diff --git a/Spatio-Temporal-Evolution/.gitignore b/Spatio-Temporal-Evolution/.gitignore
new file mode 100644
index 0000000..640d70e
--- /dev/null
+++ b/Spatio-Temporal-Evolution/.gitignore
@@ -0,0 +1,17 @@
+# Python
+__pycache__/
+*.py[cod]
+
+# Training logs (noisy, regenerable)
+checkpoints/**/*.log
+
+# NOTE: model weights (*.pt) are ignored repo-wide by the parent DevoGraph
+# .gitignore, so checkpoints are not versioned. Retrain with scripts/train_fate.py
+# (config.json + history.json are committed so the run is reproducible).
+
+# Large regenerable explainability dump (rebuild with scripts/extract_fate_explainability.py)
+checkpoints/**/fate_explainability.json
+
+# Duplicate PDFs at repo root — canonical copies live in References/
+/2402.10793v3.pdf
+/GSOC_Proposal.pdf
diff --git a/Spatio-Temporal-Evolution/DATASET_MEMO.md b/Spatio-Temporal-Evolution/DATASET_MEMO.md
new file mode 100644
index 0000000..7108811
--- /dev/null
+++ b/Spatio-Temporal-Evolution/DATASET_MEMO.md
@@ -0,0 +1,75 @@
+# Memo: Fixing the classification task — dataset options
+
+**To:** DevoWorm / DevoGraph mentors
+**From:** Barshan Mondal (GSoC — Spatio-Temporal Evolution / ESTGEL)
+**Re:** The WT-vs-RNAi classification target and which dataset can actually support it
+
+---
+
+## 1. The problem I found
+
+While preparing the explainability deliverable, I traced the training results back and found the
+classification task, as currently set up on the EPIC data, is **not learning a real signal**.
+
+- **Labels are degenerate:** `labels.csv` is **254 "perturbed/RNAi" vs 6 "control"**.
+- **Reported accuracy is the base rate:** val accuracy sits at exactly **0.9615 = 25/26** every epoch,
+  and train accuracy collapses to the identical value. The model simply predicts the majority
+  class for every embryo — it has learned nothing discriminative.
+- **The labels are also biologically wrong:** the EPIC files are almost all **wild-type embryos
+  carrying different fluorescent *reporter* strains** (`pha4`, `cnd1`, `tbx-8`, `nhr-25`, `dyf7red`, …).
+  The `blot` fluorescence *is* the reporter. Our heuristic tagged every strain without a
+  `bright`/`norfp` keyword as "RNAi-perturbed," which mislabels ~254 phenotypically wild-type
+  embryos.
+
+**Root cause:** the standard EPIC lineage set does not naturally contain a wild-type-vs-RNAi split,
+which is the graph-classification target the proposal committed to. The *pipeline* (tensor masking,
+proximity + lineage graph init, EAM / DRL / DNL, attention export) is sound and is the real
+contribution — but the discriminative task on top of it needs a dataset that has genuine
+perturbation labels.
+
+## 2. Datasets that could provide a real signal
+
+| Dataset | Perturbation labels | Depth | Per-cell data | Access |
+|---|---|---|---|---|
+| **RIKEN WDDD / SSBD "Kyoda-WormEmbryoRNAi"** | **33 WT + 1142 RNAi**, 263 genes (≥5 embryos for 189 genes) | first ~3 divisions (→ ~8-cell) | 3D nuclear coords, outlines, division timing | Open (CC BY-SA), BD5 / BDML / ome.zarr |
+| **CShaper 4D Morphological Atlas** (Nat Commun 2020) | Mostly WT (17 embryos) | 4 → 350-cell | cell shape, volume, surface area, migration, nucleus pos, **cell–cell contact** | Supplementary + repo |
+| **System-Level Morphogenesis Phenotyping** (bioRxiv 776062) | **222 WT + 758-gene RNAi** | 4 → 350-cell, 226 cells | migration trajectories, cell arrangement | availability to confirm |
+| **Digital Development DB** | 204-gene lineage phenotype annotations | lineage-level | curated phenotype flags | web DB (label source) |
+| **EPIC (current)** | ~all WT reporter strains — no real split | 350-cell, has `blot` expression | x, y, z, size, blot | already downloaded |
+
+## 3. My recommendation
+
+**Primary: adopt the RIKEN WDDD / SSBD Kyoda RNAi collection for the classification + explainability.**
+It was purpose-built as wild-type vs. RNAi, has hundreds of labeled embryos, is openly downloadable,
+and its per-nucleus 3D coordinates + division timing map directly onto our existing `X ∈ (N, d, T)`
+tensor and proximity/lineage graph init. It converts the fake 96% into a real, balanced task and even
+offers a **multi-class (per-gene) target** for richer explainability. Its one cost is developmental
+depth: only the first ~3 divisions, so smaller graphs and a weaker "growing-node / multiscale" story.
+
+**Complement: CShaper for depth and better edges.** CShaper provides true **cell–cell contact maps to
+the 350-cell stage** — far better graph edges than our current Euclidean-distance threshold — and keeps
+the deep-lineage multiscale narrative alive. Mostly WT, so it complements rather than replaces the
+labels from WDDD.
+
+**Strongest package = hybrid:** WDDD/SSBD for labeled WT-vs-RNAi classification + explainability;
+CShaper contact graphs to enrich edge construction and the multiscale story.
+
+## 4. Questions for the mentors
+
+1. Is switching the classification target to the **WDDD/SSBD RNAi** collection acceptable, given the
+   shallower developmental depth (~8-cell)?
+2. Do you prefer the **hybrid** (WDDD labels + CShaper 350-cell contact graphs), accepting the extra
+   integration work?
+3. Or should EPIC stay primary with the task **reframed** away from WT-vs-RNAi (e.g. a self-supervised
+   attention-over-development objective), transparently noting the label limitation?
+4. Any known internal DevoWorm curation of genuine EPIC RNAi/mutant embryos I should use instead?
+
+## 5. Sources
+
+- EPIC dataset — https://epic.gs.washington.edu/
+- WDDD2 (browsable) — https://wddd.riken.jp/yawddd/
+- SSBD "2-Kyoda-WormEmbryoRNAi" — https://ssbd.riken.jp/database/2/
+- Kyoda et al., *Deep Collection of Quantitative Nuclear Division Dynamics Data in RNAi-treated C. elegans Embryos* — https://www.biorxiv.org/content/10.1101/2020.10.04.325761v1
+- CShaper morphological atlas (Nat Commun 2020) — https://www.nature.com/articles/s41467-020-19863-x
+- System-level morphogenesis phenotyping (bioRxiv 776062) — https://www.biorxiv.org/content/10.1101/776062v1
+- Digital Development database (NAR 2016) — https://academic.oup.com/nar/article/44/D1/D781/2502623
diff --git a/Spatio-Temporal-Evolution/Dataset/fate/cell_fate.csv b/Spatio-Temporal-Evolution/Dataset/fate/cell_fate.csv
new file mode 100644
index 0000000..e30f41e
--- /dev/null
+++ b/Spatio-Temporal-Evolution/Dataset/fate/cell_fate.csv
@@ -0,0 +1,2770 @@
+cell,fate,fate_id,method,purity,n_leaves,n_embryos
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+ABalapapap,neuron,0,consensus,1.0,2,233
+ABalapapapa,neuron,0,consensus,1.0,1,3
+ABalapapapaa,neuron,0,exact,1.0,1,1
+ABalapapapaaa,neuron,0,ancestor,1.0,1,1
+ABalapapapaaaa,neuron,0,ancestor,1.0,1,1
+ABalapapapaaap,neuron,0,ancestor,1.0,1,1
+ABalapapapaap,neuron,0,ancestor,1.0,1,1
+ABalapapapaapa,neuron,0,ancestor,1.0,1,1
+ABalapapapaapp,neuron,0,ancestor,1.0,1,1
+ABalapapapap,neuron,0,ancestor,1.0,1,1
+ABalapapapp,neuron,0,exact,1.0,1,3
+ABalapapp,neuron,0,consensus,0.75,4,257
+ABalapappa,neuron,0,consensus,1.0,2,232
+ABalapappaa,neuron,0,consensus,1.0,1,11
+ABalapappaaa,neuron,0,exact,1.0,1,1
+ABalapappaaaa,neuron,0,ancestor,1.0,1,1
+ABalapappaaaaa,neuron,0,ancestor,1.0,1,1
+ABalapappaaaap,neuron,0,ancestor,1.0,1,1
+ABalapappaaap,neuron,0,ancestor,1.0,1,1
+ABalapappaap,neuron,0,ancestor,1.0,1,1
+ABalapappaapa,neuron,0,ancestor,1.0,1,1
+ABalapappaapaa,neuron,0,ancestor,1.0,1,1
+ABalapappaapaaa,neuron,0,ancestor,1.0,1,1
+ABalapappaapaaaa,neuron,0,ancestor,1.0,1,1
+ABalapappaapaaap,neuron,0,ancestor,1.0,1,1
+ABalapappaapaap,neuron,0,ancestor,1.0,1,1
+ABalapappaapap,neuron,0,ancestor,1.0,1,1
+ABalapappaapapa,neuron,0,ancestor,1.0,1,1
+ABalapappaapapp,neuron,0,ancestor,1.0,1,1
+ABalapappaapp,neuron,0,ancestor,1.0,1,1
+ABalapappap,neuron,0,exact,1.0,1,11
+ABalapappapa,neuron,0,ancestor,1.0,1,1
+ABalapappapaa,neuron,0,ancestor,1.0,1,1
+ABalapappapap,neuron,0,ancestor,1.0,1,1
+ABalapappapapa,neuron,0,ancestor,1.0,1,1
+ABalapappapapp,neuron,0,ancestor,1.0,1,1
+ABalapappapp,neuron,0,ancestor,1.0,1,1
+ABalapappp,mixed,11,consensus,0.5,2,232
+ABalapapppa,neuron,0,exact,1.0,1,4
+ABalapapppaa,neuron,0,ancestor,1.0,1,1
+ABalapapppap,neuron,0,ancestor,1.0,1,1
+ABalapapppp,glia,5,exact,1.0,1,4
+ABalapp,neuron,0,consensus,0.75,12,258
+ABalappa,mixed,11,consensus,0.5,4,258
+ABalappaa,neuron,0,consensus,1.0,1,256
+ABalappaaa,neuron,0,ancestor,1.0,1,228
+ABalappaaaa,neuron,0,ancestor,1.0,1,1
+ABalappaaap,neuron,0,ancestor,1.0,1,1
+ABalappaap,neuron,0,consensus,1.0,1,228
+ABalappap,mixed,11,consensus,0.333,3,256
+ABalappapa,neuron,0,consensus,1.0,1,232
+ABalappapp,mixed,11,consensus,0.5,2,232
+ABalappappa,excretory,7,exact,1.0,1,4
+ABalappappp,glia,5,exact,1.0,1,4
+ABalappp,neuron,0,consensus,0.875,8,258
+ABalapppa,neuron,0,consensus,1.0,4,257
+ABalapppaa,neuron,0,consensus,1.0,2,233
+ABalapppaaa,neuron,0,exact,1.0,1,3
+ABalapppaaaa,neuron,0,ancestor,1.0,1,1
+ABalapppaaap,neuron,0,ancestor,1.0,1,1
+ABalapppaaapa,neuron,0,ancestor,1.0,1,1
+ABalapppaaapaa,neuron,0,ancestor,1.0,1,1
+ABalapppaaapap,neuron,0,ancestor,1.0,1,1
+ABalapppaaapapa,neuron,0,ancestor,1.0,1,1
+ABalapppaaapapaa,neuron,0,ancestor,1.0,1,1
+ABalapppaaapapaaa,neuron,0,ancestor,1.0,1,1
+ABalapppaaapapaap,neuron,0,ancestor,1.0,1,1
+ABalapppaaapapap,neuron,0,ancestor,1.0,1,1
+ABalapppaaapapp,neuron,0,ancestor,1.0,1,1
+ABalapppaaapappa,neuron,0,ancestor,1.0,1,1
+ABalapppaaapappp,neuron,0,ancestor,1.0,1,1
+ABalapppaaapapppa,neuron,0,ancestor,1.0,1,1
+ABalapppaaapapppp,neuron,0,ancestor,1.0,1,1
+ABalapppaaapappppa,neuron,0,ancestor,1.0,1,1
+ABalapppaaapappppp,neuron,0,ancestor,1.0,1,1
+ABalapppaaapapppppa,neuron,0,ancestor,1.0,1,1
+ABalapppaaapapppppp,neuron,0,ancestor,1.0,1,1
+ABalapppaaapp,neuron,0,ancestor,1.0,1,1
+ABalapppaap,neuron,0,exact,1.0,1,3
+ABalapppaapa,neuron,0,ancestor,1.0,1,1
+ABalapppaapp,neuron,0,ancestor,1.0,1,1
+ABalapppap,neuron,0,consensus,1.0,2,233
+ABalapppapa,neuron,0,consensus,1.0,1,5
+ABalapppapp,neuron,0,exact,1.0,1,5
+ABalapppp,neuron,0,consensus,0.75,4,257
+ABalappppa,neuron,0,consensus,1.0,2,232
+ABalappppaa,neuron,0,consensus,1.0,1,11
+ABalappppap,neuron,0,exact,1.0,1,11
+ABalappppp,mixed,11,consensus,0.5,2,232
+ABalapppppa,neuron,0,exact,1.0,1,4
+ABalapppppp,glia,5,exact,1.0,1,4
+ABalp,mixed,11,consensus,0.388,49,258
+ABalpa,pharynx,3,consensus,0.76,25,258
+ABalpaa,pharynx,3,consensus,0.846,13,258
+ABalpaaa,pharynx,3,consensus,1.0,5,258
+ABalpaaaa,pharynx,3,consensus,1.0,3,257
+ABalpaaaaa,pharynx,3,consensus,1.0,2,231
+ABalpaaaaaa,pharynx,3,exact,1.0,1,1
+ABalpaaaaaaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaaaaaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaaaaap,pharynx,3,ancestor,1.0,1,1
+ABalpaaaaaap,pharynx,3,ancestor,1.0,1,1
+ABalpaaaaap,pharynx,3,exact,1.0,1,1
+ABalpaaaaapa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaaapaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaaapaaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaaapaap,pharynx,3,ancestor,1.0,1,1
+ABalpaaaaapap,pharynx,3,ancestor,1.0,1,1
+ABalpaaaaapp,pharynx,3,ancestor,1.0,1,1
+ABalpaaaap,pharynx,3,consensus,1.0,1,231
+ABalpaaaapa,pharynx,3,exact,1.0,1,1
+ABalpaaaapaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaaaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaaaaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaaaap,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaaaapa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaaaapp,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaaaappa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaaaappp,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaaap,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaap,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaapa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaapp,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaappa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaappaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaappaaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaappaap,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaappap,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapaappp,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapap,pharynx,3,ancestor,1.0,1,1
+ABalpaaaapp,pharynx,3,ancestor,1.0,1,1
+ABalpaaap,pharynx,3,consensus,1.0,2,257
+ABalpaaapa,pharynx,3,consensus,1.0,1,232
+ABalpaaapaa,pharynx,3,exact,1.0,1,2
+ABalpaaapap,pharynx,3,ancestor,1.0,1,2
+ABalpaaapapa,pharynx,3,ancestor,1.0,1,1
+ABalpaaapapp,pharynx,3,ancestor,1.0,1,1
+ABalpaaapappa,pharynx,3,ancestor,1.0,1,1
+ABalpaaapappp,pharynx,3,ancestor,1.0,1,1
+ABalpaaapapppa,pharynx,3,ancestor,1.0,1,1
+ABalpaaapapppp,pharynx,3,ancestor,1.0,1,1
+ABalpaaapappppa,pharynx,3,ancestor,1.0,1,1
+ABalpaaapappppaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaapappppap,pharynx,3,ancestor,1.0,1,1
+ABalpaaapappppp,pharynx,3,ancestor,1.0,1,1
+ABalpaaapp,pharynx,3,consensus,1.0,1,232
+ABalpaaappa,pharynx,3,ancestor,1.0,1,1
+ABalpaaappaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaappaaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaappaaaa,pharynx,3,ancestor,1.0,1,1
+ABalpaaappaaap,pharynx,3,ancestor,1.0,1,1
+ABalpaaappaaapa,pharynx,3,ancestor,1.0,1,1
+ABalpaaappaaapp,pharynx,3,ancestor,1.0,1,1
+ABalpaaappaap,pharynx,3,ancestor,1.0,1,1
+ABalpaaappap,pharynx,3,ancestor,1.0,1,1
+ABalpaaappapa,pharynx,3,ancestor,1.0,1,1
+ABalpaaappapp,pharynx,3,ancestor,1.0,1,1
+ABalpaaappappa,pharynx,3,ancestor,1.0,1,1
+ABalpaaappappp,pharynx,3,ancestor,1.0,1,1
+ABalpaaappp,pharynx,3,exact,1.0,1,1
+ABalpaap,pharynx,3,consensus,0.75,8,258
+ABalpaapa,pharynx,3,consensus,1.0,4,257
+ABalpaapaa,pharynx,3,consensus,1.0,2,235
+ABalpaapaaa,pharynx,3,exact,1.0,1,8
+ABalpaapaaaa,pharynx,3,ancestor,1.0,1,1
+ABalpaapaaap,pharynx,3,ancestor,1.0,1,1
+ABalpaapaap,pharynx,3,exact,1.0,1,8
+ABalpaapap,pharynx,3,consensus,1.0,2,235
+ABalpaapapa,pharynx,3,exact,1.0,1,69
+ABalpaapapp,pharynx,3,exact,1.0,1,69
+ABalpaapappa,pharynx,3,ancestor,1.0,1,1
+ABalpaapappaa,pharynx,3,ancestor,1.0,1,1
+ABalpaapappap,pharynx,3,ancestor,1.0,1,1
+ABalpaapappapa,pharynx,3,ancestor,1.0,1,1
+ABalpaapappapaa,pharynx,3,ancestor,1.0,1,1
+ABalpaapappapap,pharynx,3,ancestor,1.0,1,1
+ABalpaapappapp,pharynx,3,ancestor,1.0,1,1
+ABalpaapappp,pharynx,3,ancestor,1.0,1,1
+ABalpaapp,mixed,11,consensus,0.5,4,257
+ABalpaappa,pharynx,3,consensus,1.0,2,233
+ABalpaappaa,pharynx,3,exact,1.0,1,2
+ABalpaappaaa,pharynx,3,ancestor,1.0,1,1
+ABalpaappaap,pharynx,3,ancestor,1.0,1,1
+ABalpaappaapa,pharynx,3,ancestor,1.0,1,1
+ABalpaappaapp,pharynx,3,ancestor,1.0,1,1
+ABalpaappap,pharynx,3,exact,1.0,1,2
+ABalpaappapa,pharynx,3,ancestor,1.0,1,1
+ABalpaappapaa,pharynx,3,ancestor,1.0,1,1
+ABalpaappapap,pharynx,3,ancestor,1.0,1,1
+ABalpaappapp,pharynx,3,ancestor,1.0,1,1
+ABalpaappappa,pharynx,3,ancestor,1.0,1,1
+ABalpaappappp,pharynx,3,ancestor,1.0,1,1
+ABalpaappp,hypodermis,2,consensus,1.0,2,233
+ABalpaapppa,hypodermis,2,exact,1.0,1,2
+ABalpaapppp,hypodermis,2,exact,1.0,1,2
+ABalpaappppa,hypodermis,2,ancestor,1.0,1,1
+ABalpaappppaa,hypodermis,2,ancestor,1.0,1,1
+ABalpaappppap,hypodermis,2,ancestor,1.0,1,1
+ABalpaappppapa,hypodermis,2,ancestor,1.0,1,1
+ABalpaappppapp,hypodermis,2,ancestor,1.0,1,1
+ABalpaappppappa,hypodermis,2,ancestor,1.0,1,1
+ABalpaappppappp,hypodermis,2,ancestor,1.0,1,1
+ABalpaappppapppa,hypodermis,2,ancestor,1.0,1,1
+ABalpaappppapppp,hypodermis,2,ancestor,1.0,1,1
+ABalpaappppp,hypodermis,2,ancestor,1.0,1,1
+ABalpap,pharynx,3,consensus,0.667,12,258
+ABalpapa,mixed,11,consensus,0.5,6,258
+ABalpapaa,pharynx,3,consensus,0.667,3,257
+ABalpapaaa,mixed,11,consensus,0.5,2,232
+ABalpapaaaa,pharynx,3,exact,1.0,1,2
+ABalpapaaap,hypodermis,2,exact,1.0,1,2
+ABalpapaap,pharynx,3,consensus,1.0,1,232
+ABalpapaapa,pharynx,3,exact,1.0,1,1
+ABalpapaapaa,pharynx,3,ancestor,1.0,1,1
+ABalpapaapap,pharynx,3,ancestor,1.0,1,1
+ABalpapaapp,pharynx,3,ancestor,1.0,1,1
+ABalpapap,neuron,0,consensus,1.0,3,257
+ABalpapapa,neuron,0,consensus,1.0,2,232
+ABalpapapaa,neuron,0,exact,1.0,1,8
+ABalpapapaaa,neuron,0,ancestor,1.0,1,1
+ABalpapapaap,neuron,0,ancestor,1.0,1,1
+ABalpapapap,neuron,0,consensus,1.0,1,8
+ABalpapapp,neuron,0,consensus,1.0,1,232
+ABalpapappa,neuron,0,ancestor,1.0,1,3
+ABalpapappaa,neuron,0,ancestor,1.0,1,1
+ABalpapappap,neuron,0,ancestor,1.0,1,1
+ABalpapappp,neuron,0,exact,1.0,1,3
+ABalpapapppa,neuron,0,ancestor,1.0,1,1
+ABalpapapppp,neuron,0,ancestor,1.0,1,1
+ABalpapappppa,neuron,0,ancestor,1.0,1,1
+ABalpapappppp,neuron,0,ancestor,1.0,1,1
+ABalpapapppppa,neuron,0,ancestor,1.0,1,1
+ABalpapapppppp,neuron,0,ancestor,1.0,1,1
+ABalpapappppppa,neuron,0,ancestor,1.0,1,1
+ABalpapappppppaa,neuron,0,ancestor,1.0,1,1
+ABalpapappppppap,neuron,0,ancestor,1.0,1,1
+ABalpapappppppp,neuron,0,ancestor,1.0,1,1
+ABalpapp,pharynx,3,consensus,1.0,6,258
+ABalpappa,pharynx,3,consensus,1.0,3,257
+ABalpappaa,pharynx,3,consensus,1.0,1,236
+ABalpappaaa,pharynx,3,ancestor,1.0,1,5
+ABalpappaaaa,pharynx,3,ancestor,1.0,1,2
+ABalpappaaap,pharynx,3,ancestor,1.0,1,2
+ABalpappaaapa,pharynx,3,ancestor,1.0,1,1
+ABalpappaaapaa,pharynx,3,ancestor,1.0,1,1
+ABalpappaaapap,pharynx,3,ancestor,1.0,1,1
+ABalpappaaapp,pharynx,3,ancestor,1.0,1,1
+ABalpappaap,pharynx,3,consensus,1.0,1,5
+ABalpappap,pharynx,3,consensus,1.0,2,236
+ABalpappapa,pharynx,3,exact,1.0,1,21
+ABalpappapaa,pharynx,3,ancestor,1.0,1,1
+ABalpappapap,pharynx,3,ancestor,1.0,1,1
+ABalpappapp,pharynx,3,exact,1.0,1,21
+ABalpappp,pharynx,3,consensus,1.0,3,257
+ABalpapppa,pharynx,3,consensus,1.0,1,236
+ABalpapppaa,pharynx,3,exact,1.0,1,2
+ABalpapppaaa,pharynx,3,ancestor,1.0,1,1
+ABalpapppaap,pharynx,3,ancestor,1.0,1,1
+ABalpapppaapa,pharynx,3,ancestor,1.0,1,1
+ABalpapppaapp,pharynx,3,ancestor,1.0,1,1
+ABalpapppap,pharynx,3,ancestor,1.0,1,2
+ABalpapppapa,pharynx,3,ancestor,1.0,1,2
+ABalpapppapp,pharynx,3,ancestor,1.0,1,2
+ABalpapppp,pharynx,3,consensus,1.0,2,236
+ABalpappppa,pharynx,3,exact,1.0,1,57
+ABalpappppp,pharynx,3,exact,1.0,1,57
+ABalpp,neuron,0,consensus,0.667,24,258
+ABalppa,neuron,0,consensus,0.636,11,258
+ABalppaa,glia,5,consensus,0.667,3,258
+ABalppaaa,mixed,11,consensus,0.5,2,257
+ABalppaaaa,mixed,11,ancestor,0.5,2,231
+ABalppaaap,mixed,11,consensus,0.5,2,231
+ABalppaaapa,neuron,0,exact,1.0,1,1
+ABalppaaapp,glia,5,exact,1.0,1,1
+ABalppaap,glia,5,consensus,1.0,1,257
+ABalppaapa,glia,5,ancestor,1.0,1,232
+ABalppaapaa,glia,5,ancestor,1.0,1,2
+ABalppaapap,glia,5,ancestor,1.0,1,2
+ABalppaapapa,glia,5,ancestor,1.0,1,1
+ABalppaapapaa,glia,5,ancestor,1.0,1,1
+ABalppaapapap,glia,5,ancestor,1.0,1,1
+ABalppaapapp,glia,5,ancestor,1.0,1,1
+ABalppaapp,glia,5,consensus,1.0,1,232
+ABalppaappa,glia,5,ancestor,1.0,1,2
+ABalppaappp,glia,5,exact,1.0,1,2
+ABalppap,neuron,0,consensus,0.75,8,258
+ABalppapa,mixed,11,consensus,0.5,4,257
+ABalppapaa,mixed,11,consensus,0.5,2,233
+ABalppapap,mixed,11,consensus,0.5,2,233
+ABalppapapa,neuron,0,exact,1.0,1,2
+ABalppapapp,glia,5,exact,1.0,1,2
+ABalppapappa,glia,5,ancestor,1.0,1,1
+ABalppapappaa,glia,5,ancestor,1.0,1,1
+ABalppapappap,glia,5,ancestor,1.0,1,1
+ABalppapappapa,glia,5,ancestor,1.0,1,1
+ABalppapappapp,glia,5,ancestor,1.0,1,1
+ABalppapappappa,glia,5,ancestor,1.0,1,1
+ABalppapappappaa,glia,5,ancestor,1.0,1,1
+ABalppapappappap,glia,5,ancestor,1.0,1,1
+ABalppapappappp,glia,5,ancestor,1.0,1,1
+ABalppapappp,glia,5,ancestor,1.0,1,1
+ABalppapp,neuron,0,consensus,1.0,4,257
+ABalppappa,neuron,0,consensus,1.0,2,233
+ABalppappaa,neuron,0,exact,1.0,1,3
+ABalppappaaa,neuron,0,ancestor,1.0,1,1
+ABalppappaaaa,neuron,0,ancestor,1.0,1,1
+ABalppappaaap,neuron,0,ancestor,1.0,1,1
+ABalppappaaapa,neuron,0,ancestor,1.0,1,1
+ABalppappaaapp,neuron,0,ancestor,1.0,1,1
+ABalppappaaappa,neuron,0,ancestor,1.0,1,1
+ABalppappaaappaa,neuron,0,ancestor,1.0,1,1
+ABalppappaaappaaa,neuron,0,ancestor,1.0,1,1
+ABalppappaaappaap,neuron,0,ancestor,1.0,1,1
+ABalppappaaappap,neuron,0,ancestor,1.0,1,1
+ABalppappaaappp,neuron,0,ancestor,1.0,1,1
+ABalppappaaapppa,neuron,0,ancestor,1.0,1,1
+ABalppappaaapppp,neuron,0,ancestor,1.0,1,1
+ABalppappaap,neuron,0,ancestor,1.0,1,1
+ABalppappap,neuron,0,exact,1.0,1,3
+ABalppappp,neuron,0,consensus,1.0,2,233
+ABalppapppa,neuron,0,consensus,1.0,1,10
+ABalppapppaa,neuron,0,exact,1.0,1,1
+ABalppapppap,neuron,0,ancestor,1.0,1,1
+ABalppapppapa,neuron,0,ancestor,1.0,1,1
+ABalppapppapp,neuron,0,ancestor,1.0,1,1
+ABalppapppappa,neuron,0,ancestor,1.0,1,1
+ABalppapppappp,neuron,0,ancestor,1.0,1,1
+ABalppapppp,neuron,0,exact,1.0,1,10
+ABalppappppa,neuron,0,ancestor,1.0,1,1
+ABalppappppp,neuron,0,ancestor,1.0,1,1
+ABalppp,neuron,0,consensus,0.692,13,258
+ABalpppa,mixed,11,consensus,0.5,6,258
+ABalpppaa,glia,5,consensus,0.667,3,257
+ABalpppaaa,mixed,11,consensus,0.5,2,232
+ABalpppaaaa,neuron,0,exact,1.0,1,1
+ABalpppaaap,glia,5,exact,1.0,1,1
+ABalpppaap,glia,5,consensus,1.0,1,232
+ABalpppaapd,glia,5,exact,1.0,1,2
+ABalpppaapv,glia,5,ancestor,1.0,1,2
+ABalpppap,neuron,0,consensus,0.667,3,257
+ABalpppapa,mixed,11,consensus,0.5,2,232
+ABalpppapad,neuron,0,exact,1.0,1,2
+ABalpppapav,glia,5,exact,1.0,1,2
+ABalpppapp,neuron,0,consensus,1.0,1,232
+ABalpppappa,neuron,0,ancestor,1.0,1,7
+ABalpppappp,neuron,0,consensus,1.0,1,7
+ABalpppp,neuron,0,consensus,0.857,7,258
+ABalppppa,neuron,0,consensus,1.0,2,257
+ABalppppaa,neuron,0,consensus,1.0,1,233
+ABalppppaad,neuron,0,exact,1.0,1,3
+ABalppppaav,neuron,0,ancestor,1.0,1,3
+ABalppppap,neuron,0,consensus,1.0,1,233
+ABalppppapa,neuron,0,consensus,1.0,1,5
+ABalppppapaa,neuron,0,exact,1.0,1,1
+ABalppppapap,neuron,0,ancestor,1.0,1,1
+ABalppppapapa,neuron,0,ancestor,1.0,1,1
+ABalppppapapaa,neuron,0,ancestor,1.0,1,1
+ABalppppapapap,neuron,0,ancestor,1.0,1,1
+ABalppppapapp,neuron,0,ancestor,1.0,1,1
+ABalppppapp,neuron,0,ancestor,1.0,1,5
+ABalppppp,neuron,0,consensus,0.8,5,257
+ABalpppppa,mixed,11,consensus,0.5,2,235
+ABalpppppaa,neuron,0,exact,1.0,1,7
+ABalpppppap,glia,5,exact,1.0,1,7
+ABalpppppp,neuron,0,consensus,1.0,3,235
+ABalppppppa,neuron,0,consensus,1.0,1,45
+ABalppppppaa,neuron,0,exact,1.0,1,1
+ABalppppppaaa,neuron,0,ancestor,1.0,1,1
+ABalppppppaaaa,neuron,0,ancestor,1.0,1,1
+ABalppppppaaap,neuron,0,ancestor,1.0,1,1
+ABalppppppaap,neuron,0,ancestor,1.0,1,1
+ABalppppppaapa,neuron,0,ancestor,1.0,1,1
+ABalppppppaapp,neuron,0,ancestor,1.0,1,1
+ABalppppppap,neuron,0,ancestor,1.0,1,1
+ABalppppppp,neuron,0,consensus,1.0,2,45
+ABalpppppppa,neuron,0,exact,1.0,1,1
+ABalpppppppp,neuron,0,exact,1.0,1,1
+ABalppppppppa,neuron,0,ancestor,1.0,1,1
+ABalppppppppp,neuron,0,ancestor,1.0,1,1
+ABar,mixed,11,consensus,0.446,92,259
+ABara,pharynx,3,consensus,0.745,55,258
+ABaraa,pharynx,3,consensus,0.966,29,258
+ABaraaa,pharynx,3,consensus,0.923,13,258
+ABaraaaa,pharynx,3,consensus,1.0,5,258
+ABaraaaaa,pharynx,3,consensus,1.0,4,256
+ABaraaaaaa,pharynx,3,consensus,1.0,2,232
+ABaraaaaaaa,pharynx,3,exact,1.0,1,2
+ABaraaaaaaaa,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaap,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaapa,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaapp,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaappa,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaappp,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaapppa,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaapppp,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaappppa,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaappppp,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaapppppa,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaapppppaa,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaapppppaaa,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaapppppaap,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaapppppap,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaaapppppp,pharynx,3,ancestor,1.0,1,1
+ABaraaaaaap,pharynx,3,exact,1.0,1,2
+ABaraaaaap,pharynx,3,consensus,1.0,2,232
+ABaraaaaapa,pharynx,3,exact,1.0,1,1
+ABaraaaaapp,pharynx,3,exact,1.0,1,1
+ABaraaaap,pharynx,3,consensus,1.0,1,256
+ABaraaaapa,pharynx,3,consensus,1.0,1,230
+ABaraaaapaa,pharynx,3,ancestor,1.0,1,1
+ABaraaaapap,pharynx,3,exact,1.0,1,1
+ABaraaaapp,pharynx,3,ancestor,1.0,1,230
+ABaraaaappa,pharynx,3,ancestor,1.0,1,1
+ABaraaaappp,pharynx,3,ancestor,1.0,1,1
+ABaraaap,pharynx,3,consensus,0.875,8,258
+ABaraaapa,pharynx,3,consensus,1.0,4,257
+ABaraaapaa,pharynx,3,consensus,1.0,2,234
+ABaraaapaaa,pharynx,3,exact,1.0,1,7
+ABaraaapaap,pharynx,3,exact,1.0,1,7
+ABaraaapap,pharynx,3,consensus,1.0,2,234
+ABaraaapapa,pharynx,3,exact,1.0,1,29
+ABaraaapapp,pharynx,3,exact,1.0,1,29
+ABaraaapp,pharynx,3,consensus,0.75,4,257
+ABaraaappa,pharynx,3,consensus,1.0,2,233
+ABaraaappaa,pharynx,3,exact,1.0,1,1
+ABaraaappap,pharynx,3,exact,1.0,1,1
+ABaraaappp,mixed,11,consensus,0.5,2,233
+ABaraaapppa,pharynx,3,exact,1.0,1,3
+ABaraaapppp,hypodermis,2,exact,1.0,1,3
+ABaraaappppa,hypodermis,2,ancestor,1.0,1,1
+ABaraaappppp,hypodermis,2,ancestor,1.0,1,1
+ABaraaapppppa,hypodermis,2,ancestor,1.0,1,1
+ABaraaapppppp,hypodermis,2,ancestor,1.0,1,1
+ABaraaappppppa,hypodermis,2,ancestor,1.0,1,1
+ABaraaappppppaa,hypodermis,2,ancestor,1.0,1,1
+ABaraaappppppap,hypodermis,2,ancestor,1.0,1,1
+ABaraaappppppp,hypodermis,2,ancestor,1.0,1,1
+ABaraaapppppppa,hypodermis,2,ancestor,1.0,1,1
+ABaraaapppppppp,hypodermis,2,ancestor,1.0,1,1
+ABaraap,pharynx,3,consensus,1.0,16,258
+ABaraapa,pharynx,3,consensus,1.0,8,258
+ABaraapaa,pharynx,3,consensus,1.0,4,257
+ABaraapaaa,pharynx,3,consensus,1.0,2,231
+ABaraapaap,pharynx,3,consensus,1.0,2,231
+ABaraapaapa,pharynx,3,exact,1.0,1,7
+ABaraapaapaa,pharynx,3,ancestor,1.0,1,1
+ABaraapaapap,pharynx,3,ancestor,1.0,1,1
+ABaraapaapapa,pharynx,3,ancestor,1.0,1,1
+ABaraapaapapp,pharynx,3,ancestor,1.0,1,1
+ABaraapaapp,pharynx,3,exact,1.0,1,7
+ABaraapap,pharynx,3,consensus,1.0,4,257
+ABaraapapa,pharynx,3,consensus,1.0,2,233
+ABaraapapaa,pharynx,3,consensus,1.0,1,19
+ABaraapapap,pharynx,3,exact,1.0,1,19
+ABaraapapapa,pharynx,3,ancestor,1.0,1,1
+ABaraapapapaa,pharynx,3,ancestor,1.0,1,1
+ABaraapapapaaa,pharynx,3,ancestor,1.0,1,1
+ABaraapapapaap,pharynx,3,ancestor,1.0,1,1
+ABaraapapapaapa,pharynx,3,ancestor,1.0,1,1
+ABaraapapapaapp,pharynx,3,ancestor,1.0,1,1
+ABaraapapapaappa,pharynx,3,ancestor,1.0,1,1
+ABaraapapapaappaa,pharynx,3,ancestor,1.0,1,1
+ABaraapapapaappaaa,pharynx,3,ancestor,1.0,1,1
+ABaraapapapaappaap,pharynx,3,ancestor,1.0,1,1
+ABaraapapapaappap,pharynx,3,ancestor,1.0,1,1
+ABaraapapapaappp,pharynx,3,ancestor,1.0,1,1
+ABaraapapapap,pharynx,3,ancestor,1.0,1,1
+ABaraapapapp,pharynx,3,ancestor,1.0,1,1
+ABaraapapappa,pharynx,3,ancestor,1.0,1,1
+ABaraapapappp,pharynx,3,ancestor,1.0,1,1
+ABaraapapp,pharynx,3,consensus,1.0,2,233
+ABaraapappa,pharynx,3,exact,1.0,1,2
+ABaraapappp,pharynx,3,exact,1.0,1,2
+ABaraapapppa,pharynx,3,ancestor,1.0,1,1
+ABaraapapppp,pharynx,3,ancestor,1.0,1,1
+ABaraapp,pharynx,3,consensus,1.0,8,258
+ABaraappa,pharynx,3,consensus,1.0,4,257
+ABaraappaa,pharynx,3,consensus,1.0,2,233
+ABaraappaaa,pharynx,3,exact,1.0,1,2
+ABaraappaaaa,pharynx,3,ancestor,1.0,1,1
+ABaraappaaap,pharynx,3,ancestor,1.0,1,1
+ABaraappaap,pharynx,3,exact,1.0,1,2
+ABaraappaapa,pharynx,3,ancestor,1.0,1,1
+ABaraappaapp,pharynx,3,ancestor,1.0,1,1
+ABaraappaappa,pharynx,3,ancestor,1.0,1,1
+ABaraappaappp,pharynx,3,ancestor,1.0,1,1
+ABaraappap,pharynx,3,consensus,1.0,2,233
+ABaraappapa,pharynx,3,exact,1.0,1,9
+ABaraappapp,pharynx,3,exact,1.0,1,9
+ABaraappp,pharynx,3,consensus,1.0,4,257
+ABaraapppa,pharynx,3,consensus,1.0,2,234
+ABaraapppaa,pharynx,3,consensus,1.0,1,28
+ABaraapppap,pharynx,3,exact,1.0,1,28
+ABaraapppapa,pharynx,3,ancestor,1.0,1,1
+ABaraapppapp,pharynx,3,ancestor,1.0,1,1
+ABaraapppp,pharynx,3,consensus,1.0,2,234
+ABaraappppa,pharynx,3,exact,1.0,1,4
+ABaraappppaa,pharynx,3,ancestor,1.0,1,2
+ABaraappppaaa,pharynx,3,ancestor,1.0,1,1
+ABaraappppaaaa,pharynx,3,ancestor,1.0,1,1
+ABaraappppaaaaa,pharynx,3,ancestor,1.0,1,1
+ABaraappppaaaaaa,pharynx,3,ancestor,1.0,1,1
+ABaraappppaaaaap,pharynx,3,ancestor,1.0,1,1
+ABaraappppaaaaapa,pharynx,3,ancestor,1.0,1,1
+ABaraappppaaaaapp,pharynx,3,ancestor,1.0,1,1
+ABaraappppaaaap,pharynx,3,ancestor,1.0,1,1
+ABaraappppaaaapa,pharynx,3,ancestor,1.0,1,1
+ABaraappppaaaapp,pharynx,3,ancestor,1.0,1,1
+ABaraappppaaap,pharynx,3,ancestor,1.0,1,1
+ABaraappppaap,pharynx,3,ancestor,1.0,1,1
+ABaraappppaapa,pharynx,3,ancestor,1.0,1,1
+ABaraappppaapp,pharynx,3,ancestor,1.0,1,1
+ABaraappppaappa,pharynx,3,ancestor,1.0,1,1
+ABaraappppaappp,pharynx,3,ancestor,1.0,1,1
+ABaraappppap,pharynx,3,ancestor,1.0,1,2
+ABaraappppapa,pharynx,3,ancestor,1.0,1,1
+ABaraappppapp,pharynx,3,ancestor,1.0,1,1
+ABaraappppp,pharynx,3,exact,1.0,1,4
+ABaraapppppa,pharynx,3,ancestor,1.0,1,1
+ABaraapppppp,pharynx,3,ancestor,1.0,1,1
+ABarap,mixed,11,consensus,0.5,26,258
+ABarapa,pharynx,3,consensus,1.0,12,258
+ABarapaa,pharynx,3,consensus,1.0,6,258
+ABarapaaa,pharynx,3,consensus,1.0,3,257
+ABarapaaaa,pharynx,3,consensus,1.0,2,232
+ABarapaaaaa,pharynx,3,exact,1.0,1,2
+ABarapaaaap,pharynx,3,exact,1.0,1,2
+ABarapaaaapa,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapaa,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapap,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapapa,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapapaa,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapapaaa,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapapaap,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapapap,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapapp,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapappa,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapappaa,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapappap,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapappp,pharynx,3,ancestor,1.0,1,1
+ABarapaaaapp,pharynx,3,ancestor,1.0,1,1
+ABarapaaap,pharynx,3,consensus,1.0,1,232
+ABarapaaapa,pharynx,3,exact,1.0,1,2
+ABarapaaapaa,pharynx,3,ancestor,1.0,1,1
+ABarapaaapap,pharynx,3,ancestor,1.0,1,1
+ABarapaaapapa,pharynx,3,ancestor,1.0,1,1
+ABarapaaapapaa,pharynx,3,ancestor,1.0,1,1
+ABarapaaapapap,pharynx,3,ancestor,1.0,1,1
+ABarapaaapapp,pharynx,3,ancestor,1.0,1,1
+ABarapaaapp,pharynx,3,ancestor,1.0,1,2
+ABarapaaappa,pharynx,3,ancestor,1.0,1,1
+ABarapaaappaa,pharynx,3,ancestor,1.0,1,1
+ABarapaaappap,pharynx,3,ancestor,1.0,1,1
+ABarapaaappp,pharynx,3,ancestor,1.0,1,1
+ABarapaap,pharynx,3,consensus,1.0,3,257
+ABarapaapa,pharynx,3,consensus,1.0,1,233
+ABarapaapaa,pharynx,3,exact,1.0,1,1
+ABarapaapaaa,pharynx,3,ancestor,1.0,1,1
+ABarapaapaap,pharynx,3,ancestor,1.0,1,1
+ABarapaapaapa,pharynx,3,ancestor,1.0,1,1
+ABarapaapaapp,pharynx,3,ancestor,1.0,1,1
+ABarapaapap,pharynx,3,ancestor,1.0,1,1
+ABarapaapp,pharynx,3,consensus,1.0,2,233
+ABarapaappa,pharynx,3,exact,1.0,1,13
+ABarapaappp,pharynx,3,exact,1.0,1,13
+ABarapap,pharynx,3,consensus,1.0,6,258
+ABarapapa,pharynx,3,consensus,1.0,3,257
+ABarapapaa,pharynx,3,consensus,1.0,1,233
+ABarapapaaa,pharynx,3,ancestor,1.0,1,3
+ABarapapaaaa,pharynx,3,ancestor,1.0,1,1
+ABarapapaaap,pharynx,3,ancestor,1.0,1,1
+ABarapapaaapa,pharynx,3,ancestor,1.0,1,1
+ABarapapaaapp,pharynx,3,ancestor,1.0,1,1
+ABarapapaaappa,pharynx,3,ancestor,1.0,1,1
+ABarapapaaappp,pharynx,3,ancestor,1.0,1,1
+ABarapapaap,pharynx,3,consensus,1.0,1,3
+ABarapapap,pharynx,3,consensus,1.0,2,233
+ABarapapapa,pharynx,3,exact,1.0,1,8
+ABarapapapaa,pharynx,3,ancestor,1.0,1,2
+ABarapapapaaa,pharynx,3,ancestor,1.0,1,1
+ABarapapapaap,pharynx,3,ancestor,1.0,1,1
+ABarapapapaapa,pharynx,3,ancestor,1.0,1,1
+ABarapapapaapaa,pharynx,3,ancestor,1.0,1,1
+ABarapapapaapap,pharynx,3,ancestor,1.0,1,1
+ABarapapapaapp,pharynx,3,ancestor,1.0,1,1
+ABarapapapap,pharynx,3,ancestor,1.0,1,2
+ABarapapapp,pharynx,3,exact,1.0,1,8
+ABarapapappa,pharynx,3,ancestor,1.0,1,2
+ABarapapappp,pharynx,3,ancestor,1.0,1,2
+ABarapapp,pharynx,3,consensus,1.0,3,257
+ABarapappa,pharynx,3,consensus,1.0,1,237
+ABarapappaa,pharynx,3,exact,1.0,1,2
+ABarapappaaa,pharynx,3,ancestor,1.0,1,2
+ABarapappaaaa,pharynx,3,ancestor,1.0,1,1
+ABarapappaaap,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapa,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapaa,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapaaa,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapaaaa,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapaaaaa,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapaaaap,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapaaap,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapaaapa,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapaaapp,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapaap,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapap,pharynx,3,ancestor,1.0,1,1
+ABarapappaaapp,pharynx,3,ancestor,1.0,1,1
+ABarapappaap,pharynx,3,ancestor,1.0,1,2
+ABarapappap,pharynx,3,ancestor,1.0,1,2
+ABarapappapa,pharynx,3,ancestor,1.0,1,1
+ABarapappapaa,pharynx,3,ancestor,1.0,1,1
+ABarapappapaaa,pharynx,3,ancestor,1.0,1,1
+ABarapappapaaaa,pharynx,3,ancestor,1.0,1,1
+ABarapappapaaap,pharynx,3,ancestor,1.0,1,1
+ABarapappapaap,pharynx,3,ancestor,1.0,1,1
+ABarapappapap,pharynx,3,ancestor,1.0,1,1
+ABarapappapp,pharynx,3,ancestor,1.0,1,1
+ABarapappp,pharynx,3,consensus,1.0,2,237
+ABarapapppa,pharynx,3,exact,1.0,1,41
+ABarapapppp,pharynx,3,exact,1.0,1,41
+ABarapappppa,pharynx,3,ancestor,1.0,1,1
+ABarapappppp,pharynx,3,ancestor,1.0,1,1
+ABarapapppppa,pharynx,3,ancestor,1.0,1,1
+ABarapapppppaa,pharynx,3,ancestor,1.0,1,1
+ABarapapppppaaa,pharynx,3,ancestor,1.0,1,1
+ABarapapppppaaaa,pharynx,3,ancestor,1.0,1,1
+ABarapapppppaaap,pharynx,3,ancestor,1.0,1,1
+ABarapapppppaap,pharynx,3,ancestor,1.0,1,1
+ABarapapppppap,pharynx,3,ancestor,1.0,1,1
+ABarapapppppapa,pharynx,3,ancestor,1.0,1,1
+ABarapapppppapp,pharynx,3,ancestor,1.0,1,1
+ABarapapppppp,pharynx,3,ancestor,1.0,1,1
+ABarapp,neuron,0,consensus,0.643,14,258
+ABarappa,mixed,11,consensus,0.5,6,258
+ABarappaa,mixed,11,consensus,0.5,2,256
+ABarappaaa,pharynx,3,consensus,1.0,1,232
+ABarappaaaa,pharynx,3,exact,1.0,1,3
+ABarappaaap,pharynx,3,ancestor,1.0,1,3
+ABarappaap,hypodermis,2,consensus,1.0,1,232
+ABarappaapa,hypodermis,2,exact,1.0,1,4
+ABarappaapaa,hypodermis,2,ancestor,1.0,1,1
+ABarappaapaaa,hypodermis,2,ancestor,1.0,1,1
+ABarappaapaap,hypodermis,2,ancestor,1.0,1,1
+ABarappaapap,hypodermis,2,ancestor,1.0,1,1
+ABarappaapapa,hypodermis,2,ancestor,1.0,1,1
+ABarappaapapaa,hypodermis,2,ancestor,1.0,1,1
+ABarappaapapaaa,hypodermis,2,ancestor,1.0,1,1
+ABarappaapapaap,hypodermis,2,ancestor,1.0,1,1
+ABarappaapapap,hypodermis,2,ancestor,1.0,1,1
+ABarappaapapp,hypodermis,2,ancestor,1.0,1,1
+ABarappaapp,hypodermis,2,ancestor,1.0,1,4
+ABarappaappa,hypodermis,2,ancestor,1.0,1,1
+ABarappaappp,hypodermis,2,ancestor,1.0,1,1
+ABarappaapppa,hypodermis,2,ancestor,1.0,1,1
+ABarappaapppp,hypodermis,2,ancestor,1.0,1,1
+ABarappap,neuron,0,consensus,0.75,4,256
+ABarappapa,neuron,0,consensus,1.0,2,232
+ABarappapaa,neuron,0,exact,1.0,1,6
+ABarappapap,neuron,0,consensus,1.0,1,6
+ABarappapapa,neuron,0,ancestor,1.0,1,1
+ABarappapapp,neuron,0,exact,1.0,1,1
+ABarappapappa,neuron,0,ancestor,1.0,1,1
+ABarappapappp,neuron,0,ancestor,1.0,1,1
+ABarappapp,mixed,11,consensus,0.5,2,232
+ABarappappa,muscle,1,exact,1.0,1,3
+ABarappappp,neuron,0,exact,1.0,1,3
+ABarappapppa,neuron,0,ancestor,1.0,1,1
+ABarappapppp,neuron,0,ancestor,1.0,1,1
+ABarappappppa,neuron,0,ancestor,1.0,1,1
+ABarappappppp,neuron,0,ancestor,1.0,1,1
+ABarappapppppa,neuron,0,ancestor,1.0,1,1
+ABarappapppppp,neuron,0,ancestor,1.0,1,1
+ABarappp,neuron,0,consensus,0.75,8,258
+ABarapppa,mixed,11,consensus,0.5,4,257
+ABarapppaa,mixed,11,consensus,0.5,2,233
+ABarapppaaa,neuron,0,exact,1.0,1,1
+ABarapppaap,glia,5,exact,1.0,1,1
+ABarapppap,mixed,11,consensus,0.5,2,233
+ABarapppapa,neuron,0,exact,1.0,1,2
+ABarapppapp,glia,5,exact,1.0,1,2
+ABarapppp,neuron,0,consensus,1.0,4,257
+ABarappppa,neuron,0,consensus,1.0,2,233
+ABarappppaa,neuron,0,exact,1.0,1,4
+ABarappppaaa,neuron,0,ancestor,1.0,1,1
+ABarappppaap,neuron,0,ancestor,1.0,1,1
+ABarappppap,neuron,0,exact,1.0,1,4
+ABarappppapa,neuron,0,ancestor,1.0,1,1
+ABarappppapaa,neuron,0,ancestor,1.0,1,1
+ABarappppapap,neuron,0,ancestor,1.0,1,1
+ABarappppapapa,neuron,0,ancestor,1.0,1,1
+ABarappppapapaa,neuron,0,ancestor,1.0,1,1
+ABarappppapapap,neuron,0,ancestor,1.0,1,1
+ABarappppapapp,neuron,0,ancestor,1.0,1,1
+ABarappppapp,neuron,0,ancestor,1.0,1,1
+ABarappppp,neuron,0,consensus,1.0,2,233
+ABarapppppa,neuron,0,consensus,1.0,1,7
+ABarapppppaa,neuron,0,exact,1.0,1,1
+ABarapppppap,neuron,0,ancestor,1.0,1,1
+ABarapppppp,neuron,0,exact,1.0,1,7
+ABarappppppa,neuron,0,ancestor,1.0,1,1
+ABarappppppp,neuron,0,ancestor,1.0,1,1
+ABarp,mixed,11,consensus,0.541,37,258
+ABarpa,mixed,11,consensus,0.5,20,258
+ABarpaa,glia,5,consensus,0.6,10,258
+ABarpaaa,glia,5,consensus,1.0,6,258
+ABarpaaaa,glia,5,consensus,1.0,4,256
+ABarpaaaaa,glia,5,consensus,1.0,2,232
+ABarpaaaaal,glia,5,exact,1.0,1,1
+ABarpaaaaar,glia,5,exact,1.0,1,1
+ABarpaaaap,glia,5,consensus,1.0,2,232
+ABarpaaap,glia,5,consensus,1.0,2,256
+ABarpaaapa,glia,5,consensus,1.0,2,231
+ABarpaaapaa,glia,5,exact,1.0,1,1
+ABarpaaapap,glia,5,exact,1.0,1,1
+ABarpaaapapa,glia,5,ancestor,1.0,1,1
+ABarpaaapapaa,glia,5,ancestor,1.0,1,1
+ABarpaaapapap,glia,5,ancestor,1.0,1,1
+ABarpaaapapapa,glia,5,ancestor,1.0,1,1
+ABarpaaapapapp,glia,5,ancestor,1.0,1,1
+ABarpaaapapappa,glia,5,ancestor,1.0,1,1
+ABarpaaapapappaa,glia,5,ancestor,1.0,1,1
+ABarpaaapapappap,glia,5,ancestor,1.0,1,1
+ABarpaaapapappapa,glia,5,ancestor,1.0,1,1
+ABarpaaapapappapp,glia,5,ancestor,1.0,1,1
+ABarpaaapapappp,glia,5,ancestor,1.0,1,1
+ABarpaaapapapppa,glia,5,ancestor,1.0,1,1
+ABarpaaapapapppp,glia,5,ancestor,1.0,1,1
+ABarpaaapapp,glia,5,ancestor,1.0,1,1
+ABarpaaapappa,glia,5,ancestor,1.0,1,1
+ABarpaaapappp,glia,5,ancestor,1.0,1,1
+ABarpaaapp,glia,5,ancestor,1.0,2,231
+ABarpaap,hypodermis,2,consensus,1.0,4,258
+ABarpaapa,hypodermis,2,consensus,1.0,2,257
+ABarpaapaa,hypodermis,2,exact,1.0,1,233
+ABarpaapaaa,hypodermis,2,ancestor,1.0,1,1
+ABarpaapaap,hypodermis,2,ancestor,1.0,1,1
+ABarpaapap,hypodermis,2,exact,1.0,1,233
+ABarpaapp,hypodermis,2,consensus,1.0,2,257
+ABarpaappa,hypodermis,2,exact,1.0,1,233
+ABarpaappp,hypodermis,2,exact,1.0,1,233
+ABarpap,hypodermis,2,consensus,0.6,10,258
+ABarpapa,mixed,11,consensus,0.5,6,258
+ABarpapaa,neuron,0,consensus,0.75,4,257
+ABarpapaaa,mixed,11,consensus,0.5,2,232
+ABarpapaaaa,neuron,0,exact,1.0,1,2
+ABarpapaaaaa,neuron,0,ancestor,1.0,1,1
+ABarpapaaaaaa,neuron,0,ancestor,1.0,1,1
+ABarpapaaaaaaa,neuron,0,ancestor,1.0,1,1
+ABarpapaaaaaaaa,neuron,0,ancestor,1.0,1,1
+ABarpapaaaaaaaaa,neuron,0,ancestor,1.0,1,1
+ABarpapaaaaaaaap,neuron,0,ancestor,1.0,1,1
+ABarpapaaaaaaap,neuron,0,ancestor,1.0,1,1
+ABarpapaaaaaap,neuron,0,ancestor,1.0,1,1
+ABarpapaaaaap,neuron,0,ancestor,1.0,1,1
+ABarpapaaaap,neuron,0,ancestor,1.0,1,1
+ABarpapaaaapa,neuron,0,ancestor,1.0,1,1
+ABarpapaaaapp,neuron,0,ancestor,1.0,1,1
+ABarpapaaap,death,9,exact,1.0,1,2
+ABarpapaaapa,death,9,ancestor,1.0,1,1
+ABarpapaaapaa,death,9,ancestor,1.0,1,1
+ABarpapaaapap,death,9,ancestor,1.0,1,1
+ABarpapaaapapa,death,9,ancestor,1.0,1,1
+ABarpapaaapapp,death,9,ancestor,1.0,1,1
+ABarpapaaapappa,death,9,ancestor,1.0,1,1
+ABarpapaaapappp,death,9,ancestor,1.0,1,1
+ABarpapaaapp,death,9,ancestor,1.0,1,1
+ABarpapaap,neuron,0,consensus,1.0,2,232
+ABarpapaapa,neuron,0,ancestor,1.0,2,4
+ABarpapaapp,neuron,0,consensus,1.0,2,4
+ABarpapaappa,neuron,0,exact,1.0,1,1
+ABarpapaappaa,neuron,0,ancestor,1.0,1,1
+ABarpapaappap,neuron,0,ancestor,1.0,1,1
+ABarpapaappp,neuron,0,exact,1.0,1,1
+ABarpapaapppa,neuron,0,ancestor,1.0,1,1
+ABarpapaapppaa,neuron,0,ancestor,1.0,1,1
+ABarpapaapppap,neuron,0,ancestor,1.0,1,1
+ABarpapaapppp,neuron,0,ancestor,1.0,1,1
+ABarpapaappppa,neuron,0,ancestor,1.0,1,1
+ABarpapaappppp,neuron,0,ancestor,1.0,1,1
+ABarpapap,hypodermis,2,consensus,1.0,2,257
+ABarpapapa,hypodermis,2,exact,1.0,1,232
+ABarpapapp,hypodermis,2,exact,1.0,1,232
+ABarpapappa,hypodermis,2,ancestor,1.0,1,2
+ABarpapappp,hypodermis,2,ancestor,1.0,1,2
+ABarpapapppa,hypodermis,2,ancestor,1.0,1,1
+ABarpapapppp,hypodermis,2,ancestor,1.0,1,1
+ABarpapappppa,hypodermis,2,ancestor,1.0,1,1
+ABarpapappppp,hypodermis,2,ancestor,1.0,1,1
+ABarpapp,hypodermis,2,consensus,1.0,4,258
+ABarpappa,hypodermis,2,consensus,1.0,2,257
+ABarpappaa,hypodermis,2,exact,1.0,1,233
+ABarpappaaa,hypodermis,2,ancestor,1.0,1,1
+ABarpappaaaa,hypodermis,2,ancestor,1.0,1,1
+ABarpappaaap,hypodermis,2,ancestor,1.0,1,1
+ABarpappaaapa,hypodermis,2,ancestor,1.0,1,1
+ABarpappaaapp,hypodermis,2,ancestor,1.0,1,1
+ABarpappaap,hypodermis,2,ancestor,1.0,1,1
+ABarpappaapa,hypodermis,2,ancestor,1.0,1,1
+ABarpappaapaa,hypodermis,2,ancestor,1.0,1,1
+ABarpappaapap,hypodermis,2,ancestor,1.0,1,1
+ABarpappaapp,hypodermis,2,ancestor,1.0,1,1
+ABarpappaappa,hypodermis,2,ancestor,1.0,1,1
+ABarpappaappaa,hypodermis,2,ancestor,1.0,1,1
+ABarpappaappap,hypodermis,2,ancestor,1.0,1,1
+ABarpappaappp,hypodermis,2,ancestor,1.0,1,1
+ABarpappaapppa,hypodermis,2,ancestor,1.0,1,1
+ABarpappaapppp,hypodermis,2,ancestor,1.0,1,1
+ABarpappap,hypodermis,2,exact,1.0,1,233
+ABarpappapa,hypodermis,2,ancestor,1.0,1,1
+ABarpappapp,hypodermis,2,ancestor,1.0,1,1
+ABarpappappa,hypodermis,2,ancestor,1.0,1,1
+ABarpappappp,hypodermis,2,ancestor,1.0,1,1
+ABarpappp,hypodermis,2,consensus,1.0,2,257
+ABarpapppa,hypodermis,2,exact,1.0,1,232
+ABarpapppaa,hypodermis,2,ancestor,1.0,1,1
+ABarpapppap,hypodermis,2,ancestor,1.0,1,1
+ABarpapppp,hypodermis,2,exact,1.0,1,232
+ABarpappppa,hypodermis,2,ancestor,1.0,1,1
+ABarpappppp,hypodermis,2,ancestor,1.0,1,1
+ABarpp,mixed,11,consensus,0.588,17,258
+ABarppa,hypodermis,2,consensus,0.625,8,258
+ABarppaa,mixed,11,consensus,0.5,4,258
+ABarppaaa,glia,5,consensus,1.0,2,256
+ABarppaaaa,glia,5,exact,1.0,1,233
+ABarppaaaaa,glia,5,ancestor,1.0,1,1
+ABarppaaaaaa,glia,5,ancestor,1.0,1,1
+ABarppaaaaap,glia,5,ancestor,1.0,1,1
+ABarppaaaap,glia,5,ancestor,1.0,1,1
+ABarppaaap,glia,5,exact,1.0,1,233
+ABarppaap,mixed,11,consensus,0.5,2,256
+ABarppaapa,hypodermis,2,exact,1.0,1,234
+ABarppaapaa,hypodermis,2,ancestor,1.0,1,1
+ABarppaapaaa,hypodermis,2,ancestor,1.0,1,1
+ABarppaapaap,hypodermis,2,ancestor,1.0,1,1
+ABarppaapap,hypodermis,2,ancestor,1.0,1,1
+ABarppaapp,excretory,7,consensus,1.0,1,234
+ABarppap,hypodermis,2,consensus,1.0,4,258
+ABarppapa,hypodermis,2,consensus,1.0,2,256
+ABarppapaa,hypodermis,2,exact,1.0,1,233
+ABarppapap,hypodermis,2,exact,1.0,1,233
+ABarppapp,hypodermis,2,consensus,1.0,2,256
+ABarppappa,hypodermis,2,exact,1.0,1,233
+ABarppappaa,hypodermis,2,ancestor,1.0,1,1
+ABarppappap,hypodermis,2,ancestor,1.0,1,1
+ABarppappp,hypodermis,2,exact,1.0,1,233
+ABarppapppa,hypodermis,2,ancestor,1.0,1,1
+ABarppapppp,hypodermis,2,ancestor,1.0,1,1
+ABarppp,mixed,11,consensus,0.556,9,258
+ABarpppa,mixed,11,consensus,0.4,5,258
+ABarpppaa,glia,5,consensus,1.0,2,257
+ABarpppaaa,glia,5,exact,1.0,1,234
+ABarpppaap,glia,5,exact,1.0,1,234
+ABarpppap,mixed,11,consensus,0.333,3,257
+ABarpppapa,hypodermis,2,exact,1.0,1,234
+ABarpppapp,mixed,11,consensus,0.5,2,234
+ABarpppp,hypodermis,2,consensus,1.0,4,258
+ABarppppa,hypodermis,2,consensus,1.0,2,256
+ABarppppaa,hypodermis,2,exact,1.0,1,233
+ABarppppap,hypodermis,2,exact,1.0,1,233
+ABarppppp,hypodermis,2,consensus,1.0,2,256
+ABarpppppa,hypodermis,2,exact,1.0,1,233
+ABarpppppp,hypodermis,2,exact,1.0,1,233
+ABarppppppa,hypodermis,2,ancestor,1.0,1,1
+ABarppppppp,hypodermis,2,ancestor,1.0,1,1
+ABp,mixed,11,consensus,0.448,210,252
+ABpl,mixed,11,consensus,0.408,103,260
+ABpla,mixed,11,consensus,0.455,44,260
+ABplaa,mixed,11,consensus,0.5,22,260
+ABplaaa,hypodermis,2,consensus,0.6,10,258
+ABplaaaa,mixed,11,consensus,0.5,6,258
+ABplaaaaa,neuron,0,consensus,0.75,4,257
+ABplaaaaaa,mixed,11,consensus,0.5,2,232
+ABplaaaaap,neuron,0,consensus,1.0,2,232
+ABplaaaaapa,neuron,0,ancestor,1.0,2,7
+ABplaaaaapaa,neuron,0,ancestor,1.0,2,1
+ABplaaaaapap,neuron,0,ancestor,1.0,2,1
+ABplaaaaapp,neuron,0,consensus,1.0,2,7
+ABplaaaaappa,neuron,0,exact,1.0,1,1
+ABplaaaaappp,neuron,0,exact,1.0,1,1
+ABplaaaap,hypodermis,2,consensus,1.0,2,257
+ABplaaaapa,hypodermis,2,exact,1.0,1,233
+ABplaaaapp,hypodermis,2,exact,1.0,1,233
+ABplaaap,hypodermis,2,consensus,1.0,4,258
+ABplaaapa,hypodermis,2,consensus,1.0,2,257
+ABplaaapaa,hypodermis,2,exact,1.0,1,232
+ABplaaapaaa,hypodermis,2,ancestor,1.0,1,1
+ABplaaapaaaa,hypodermis,2,ancestor,1.0,1,1
+ABplaaapaaaaa,hypodermis,2,ancestor,1.0,1,1
+ABplaaapaaaaaa,hypodermis,2,ancestor,1.0,1,1
+ABplaaapaaaaap,hypodermis,2,ancestor,1.0,1,1
+ABplaaapaaaap,hypodermis,2,ancestor,1.0,1,1
+ABplaaapaaap,hypodermis,2,ancestor,1.0,1,1
+ABplaaapaap,hypodermis,2,ancestor,1.0,1,1
+ABplaaapap,hypodermis,2,exact,1.0,1,232
+ABplaaapp,hypodermis,2,consensus,1.0,2,257
+ABplaaappa,hypodermis,2,exact,1.0,1,232
+ABplaaappaa,hypodermis,2,ancestor,1.0,1,1
+ABplaaappaaa,hypodermis,2,ancestor,1.0,1,1
+ABplaaappaap,hypodermis,2,ancestor,1.0,1,1
+ABplaaappap,hypodermis,2,ancestor,1.0,1,1
+ABplaaappapa,hypodermis,2,ancestor,1.0,1,1
+ABplaaappapp,hypodermis,2,ancestor,1.0,1,1
+ABplaaappappa,hypodermis,2,ancestor,1.0,1,1
+ABplaaappappp,hypodermis,2,ancestor,1.0,1,1
+ABplaaappp,hypodermis,2,exact,1.0,1,232
+ABplaaapppa,hypodermis,2,ancestor,1.0,1,1
+ABplaaapppp,hypodermis,2,ancestor,1.0,1,1
+ABplaap,mixed,11,consensus,0.417,12,258
+ABplaapa,mixed,11,consensus,0.5,8,258
+ABplaapaa,mixed,11,consensus,0.5,4,257
+ABplaapaaa,mixed,11,consensus,0.5,2,233
+ABplaapaaaa,hypodermis,2,exact,1.0,1,2
+ABplaapaaaaa,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaaaa,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaaaaa,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaaaaaa,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaaaaap,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaaaaapa,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaaaaapp,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaaaap,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaaaapa,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaaaapp,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaaap,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaap,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaapa,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaapaa,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaapap,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaapapa,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaapapaa,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaapapap,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaapapp,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaaapp,hypodermis,2,ancestor,1.0,1,1
+ABplaapaaap,glia,5,exact,1.0,1,2
+ABplaapaaapa,glia,5,ancestor,1.0,1,1
+ABplaapaaapaa,glia,5,ancestor,1.0,1,1
+ABplaapaaapap,glia,5,ancestor,1.0,1,1
+ABplaapaaapapa,glia,5,ancestor,1.0,1,1
+ABplaapaaapapp,glia,5,ancestor,1.0,1,1
+ABplaapaaapappa,glia,5,ancestor,1.0,1,1
+ABplaapaaapappp,glia,5,ancestor,1.0,1,1
+ABplaapaaapp,glia,5,ancestor,1.0,1,1
+ABplaapaaappa,glia,5,ancestor,1.0,1,1
+ABplaapaaappp,glia,5,ancestor,1.0,1,1
+ABplaapaap,mixed,11,consensus,0.5,2,233
+ABplaapaapa,neuron,0,exact,1.0,1,5
+ABplaapaapp,glia,5,exact,1.0,1,5
+ABplaapap,neuron,0,consensus,0.75,4,257
+ABplaapapa,mixed,11,consensus,0.5,2,232
+ABplaapapp,neuron,0,consensus,1.0,2,232
+ABplaapappa,neuron,0,exact,1.0,1,8
+ABplaapappp,neuron,0,consensus,1.0,1,8
+ABplaapp,hypodermis,2,consensus,1.0,4,258
+ABplaappa,hypodermis,2,consensus,1.0,2,257
+ABplaappaa,hypodermis,2,exact,1.0,1,232
+ABplaappap,hypodermis,2,exact,1.0,1,232
+ABplaappapa,hypodermis,2,ancestor,1.0,1,1
+ABplaappapp,hypodermis,2,ancestor,1.0,1,1
+ABplaappp,hypodermis,2,consensus,1.0,2,257
+ABplaapppa,hypodermis,2,exact,1.0,1,234
+ABplaapppaa,hypodermis,2,ancestor,1.0,1,1
+ABplaapppap,hypodermis,2,ancestor,1.0,1,1
+ABplaapppp,hypodermis,2,exact,1.0,1,234
+ABplaappppa,hypodermis,2,ancestor,1.0,1,1
+ABplaappppp,hypodermis,2,ancestor,1.0,1,1
+ABplap,mixed,11,consensus,0.409,22,260
+ABplapa,mixed,11,consensus,0.462,13,260
+ABplapaa,neuron,0,consensus,0.714,7,260
+ABplapaaa,neuron,0,consensus,1.0,5,259
+ABplapaaaa,neuron,0,consensus,1.0,2,236
+ABplapaaaaa,neuron,0,ancestor,1.0,2,4
+ABplapaaaap,neuron,0,consensus,1.0,2,4
+ABplapaaaapa,neuron,0,exact,1.0,1,1
+ABplapaaaapp,neuron,0,exact,1.0,1,1
+ABplapaaaappa,neuron,0,ancestor,1.0,1,1
+ABplapaaaappp,neuron,0,ancestor,1.0,1,1
+ABplapaaap,neuron,0,consensus,1.0,3,236
+ABplapaaapa,neuron,0,consensus,1.0,2,6
+ABplapaaapp,neuron,0,exact,1.0,1,6
+ABplapaap,mixed,11,consensus,0.5,2,259
+ABplapaapa,glia,5,exact,1.0,1,236
+ABplapaapaa,glia,5,ancestor,1.0,1,1
+ABplapaapap,glia,5,ancestor,1.0,1,1
+ABplapaapp,hypodermis,2,exact,1.0,1,236
+ABplapap,mixed,11,consensus,0.5,6,260
+ABplapapa,hypodermis,2,consensus,0.667,3,259
+ABplapapaa,mixed,11,consensus,0.5,2,236
+ABplapapap,hypodermis,2,exact,1.0,1,236
+ABplapapapa,hypodermis,2,ancestor,1.0,1,1
+ABplapapapp,hypodermis,2,ancestor,1.0,1,1
+ABplapapp,mixed,11,consensus,0.333,3,259
+ABplapappa,hypodermis,2,exact,1.0,1,236
+ABplapappp,mixed,11,consensus,0.5,2,236
+ABplapapppa,mixed,11,ancestor,0.5,2,4
+ABplapapppp,mixed,11,consensus,0.5,2,4
+ABplapp,mixed,11,consensus,0.556,9,260
+ABplappa,hypodermis,2,consensus,1.0,4,260
+ABplappaa,hypodermis,2,consensus,1.0,2,259
+ABplappaaa,hypodermis,2,exact,1.0,1,236
+ABplappaaaa,hypodermis,2,ancestor,1.0,1,1
+ABplappaaap,hypodermis,2,ancestor,1.0,1,1
+ABplappaap,hypodermis,2,exact,1.0,1,236
+ABplappaapa,hypodermis,2,ancestor,1.0,1,1
+ABplappaapp,hypodermis,2,ancestor,1.0,1,1
+ABplappap,hypodermis,2,consensus,1.0,2,259
+ABplappapa,hypodermis,2,exact,1.0,1,235
+ABplappapp,hypodermis,2,exact,1.0,1,235
+ABplappp,mixed,11,consensus,0.4,5,260
+ABplapppa,neuron,0,consensus,0.667,3,259
+ABplapppaa,neuron,0,consensus,1.0,1,237
+ABplapppaaa,neuron,0,exact,1.0,1,2
+ABplapppaap,neuron,0,ancestor,1.0,1,2
+ABplapppap,mixed,11,consensus,0.5,2,237
+ABplapppapa,mixed,11,ancestor,0.5,2,5
+ABplapppapaa,mixed,11,ancestor,0.5,2,1
+ABplapppapap,mixed,11,ancestor,0.5,2,1
+ABplapppapp,mixed,11,consensus,0.5,2,5
+ABplapppappa,muscle,1,exact,1.0,1,1
+ABplapppappp,neuron,0,exact,1.0,1,1
+ABplapppp,mixed,11,consensus,0.5,2,259
+ABplappppa,hypodermis,2,exact,1.0,1,236
+ABplappppaa,hypodermis,2,ancestor,1.0,1,1
+ABplappppap,hypodermis,2,ancestor,1.0,1,1
+ABplappppp,glia,5,exact,1.0,1,236
+ABplapppppa,glia,5,ancestor,1.0,1,1
+ABplapppppp,glia,5,ancestor,1.0,1,1
+ABplp,mixed,11,consensus,0.458,59,260
+ABplpa,mixed,11,consensus,0.5,30,260
+ABplpaa,neuron,0,consensus,0.625,16,258
+ABplpaaa,mixed,11,consensus,0.5,8,258
+ABplpaaaa,mixed,11,consensus,0.25,4,257
+ABplpaaaaa,mixed,11,consensus,0.5,2,233
+ABplpaaaaaa,neuron,0,exact,1.0,1,4
+ABplpaaaaaaa,neuron,0,ancestor,1.0,1,1
+ABplpaaaaaap,neuron,0,ancestor,1.0,1,1
+ABplpaaaaaapa,neuron,0,ancestor,1.0,1,1
+ABplpaaaaaapp,neuron,0,ancestor,1.0,1,1
+ABplpaaaaaappa,neuron,0,ancestor,1.0,1,1
+ABplpaaaaaappaa,neuron,0,ancestor,1.0,1,1
+ABplpaaaaaappap,neuron,0,ancestor,1.0,1,1
+ABplpaaaaaappp,neuron,0,ancestor,1.0,1,1
+ABplpaaaaap,glia,5,exact,1.0,1,4
+ABplpaaaaapa,glia,5,ancestor,1.0,1,1
+ABplpaaaaapaa,glia,5,ancestor,1.0,1,1
+ABplpaaaaapap,glia,5,ancestor,1.0,1,1
+ABplpaaaaapp,glia,5,ancestor,1.0,1,1
+ABplpaaaap,mixed,11,consensus,0.5,2,233
+ABplpaaaapa,excretory,7,exact,1.0,1,11
+ABplpaaaapaa,excretory,7,ancestor,1.0,1,2
+ABplpaaaapaaa,excretory,7,ancestor,1.0,1,2
+ABplpaaaapaaaa,excretory,7,ancestor,1.0,1,2
+ABplpaaaapaaaaa,excretory,7,ancestor,1.0,1,1
+ABplpaaaapaaaap,excretory,7,ancestor,1.0,1,1
+ABplpaaaapaaap,excretory,7,ancestor,1.0,1,2
+ABplpaaaapaap,excretory,7,ancestor,1.0,1,2
+ABplpaaaapaapa,excretory,7,ancestor,1.0,1,1
+ABplpaaaapaapp,excretory,7,ancestor,1.0,1,1
+ABplpaaaapap,excretory,7,ancestor,1.0,1,2
+ABplpaaaapapa,excretory,7,ancestor,1.0,1,2
+ABplpaaaapapp,excretory,7,ancestor,1.0,1,2
+ABplpaaaapappa,excretory,7,ancestor,1.0,1,1
+ABplpaaaapappaa,excretory,7,ancestor,1.0,1,1
+ABplpaaaapappap,excretory,7,ancestor,1.0,1,1
+ABplpaaaapappapa,excretory,7,ancestor,1.0,1,1
+ABplpaaaapappapp,excretory,7,ancestor,1.0,1,1
+ABplpaaaapappp,excretory,7,ancestor,1.0,1,1
+ABplpaaaapapppa,excretory,7,ancestor,1.0,1,1
+ABplpaaaapapppaa,excretory,7,ancestor,1.0,1,1
+ABplpaaaapapppap,excretory,7,ancestor,1.0,1,1
+ABplpaaaapapppp,excretory,7,ancestor,1.0,1,1
+ABplpaaaapappppa,excretory,7,ancestor,1.0,1,1
+ABplpaaaapappppp,excretory,7,ancestor,1.0,1,1
+ABplpaaaapp,muscle,1,exact,1.0,1,11
+ABplpaaaappa,muscle,1,ancestor,1.0,1,1
+ABplpaaaappaa,muscle,1,ancestor,1.0,1,1
+ABplpaaaappap,muscle,1,ancestor,1.0,1,1
+ABplpaaaappp,muscle,1,ancestor,1.0,1,1
+ABplpaaap,neuron,0,consensus,0.75,4,257
+ABplpaaapa,mixed,11,consensus,0.5,2,232
+ABplpaaapaa,neuron,0,exact,1.0,1,1
+ABplpaaapap,glia,5,exact,1.0,1,1
+ABplpaaapp,neuron,0,consensus,1.0,2,232
+ABplpaaappa,neuron,0,consensus,1.0,1,4
+ABplpaaappp,neuron,0,exact,1.0,1,4
+ABplpaap,neuron,0,consensus,0.75,8,258
+ABplpaapa,mixed,11,consensus,0.5,4,257
+ABplpaapaa,neuron,0,consensus,1.0,2,232
+ABplpaapaaa,neuron,0,exact,1.0,1,1
+ABplpaapaaaa,neuron,0,ancestor,1.0,1,1
+ABplpaapaaaaa,neuron,0,ancestor,1.0,1,1
+ABplpaapaaaap,neuron,0,ancestor,1.0,1,1
+ABplpaapaaap,neuron,0,ancestor,1.0,1,1
+ABplpaapaaapa,neuron,0,ancestor,1.0,1,1
+ABplpaapaaapp,neuron,0,ancestor,1.0,1,1
+ABplpaapaaappa,neuron,0,ancestor,1.0,1,1
+ABplpaapaaappp,neuron,0,ancestor,1.0,1,1
+ABplpaapaap,neuron,0,exact,1.0,1,1
+ABplpaapaapa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaaa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaaaa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaaap,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaaapa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaaapp,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaap,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaapa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaapaa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaapap,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaapp,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaappa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaappaa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaappaaa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaappaap,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaappap,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaappp,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaapppa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaapppaa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaapppap,neuron,0,ancestor,1.0,1,1
+ABplpaapaapaapppp,neuron,0,ancestor,1.0,1,1
+ABplpaapaapap,neuron,0,ancestor,1.0,1,1
+ABplpaapaapp,neuron,0,ancestor,1.0,1,1
+ABplpaapaappa,neuron,0,ancestor,1.0,1,1
+ABplpaapaappp,neuron,0,ancestor,1.0,1,1
+ABplpaapaapppa,neuron,0,ancestor,1.0,1,1
+ABplpaapaapppp,neuron,0,ancestor,1.0,1,1
+ABplpaapap,mixed,11,consensus,0.5,2,232
+ABplpaapapa,glia,5,exact,1.0,1,1
+ABplpaapapaa,glia,5,ancestor,1.0,1,1
+ABplpaapapaaa,glia,5,ancestor,1.0,1,1
+ABplpaapapaap,glia,5,ancestor,1.0,1,1
+ABplpaapapap,glia,5,ancestor,1.0,1,1
+ABplpaapapp,death,9,exact,1.0,1,1
+ABplpaapappa,death,9,ancestor,1.0,1,1
+ABplpaapappaa,death,9,ancestor,1.0,1,1
+ABplpaapappaaa,death,9,ancestor,1.0,1,1
+ABplpaapappaap,death,9,ancestor,1.0,1,1
+ABplpaapappaapa,death,9,ancestor,1.0,1,1
+ABplpaapappaapp,death,9,ancestor,1.0,1,1
+ABplpaapappap,death,9,ancestor,1.0,1,1
+ABplpaapappp,death,9,ancestor,1.0,1,1
+ABplpaapapppa,death,9,ancestor,1.0,1,1
+ABplpaapapppp,death,9,ancestor,1.0,1,1
+ABplpaapp,neuron,0,consensus,1.0,4,257
+ABplpaappa,neuron,0,consensus,1.0,2,233
+ABplpaappaa,neuron,0,exact,1.0,1,6
+ABplpaappap,neuron,0,exact,1.0,1,6
+ABplpaappp,neuron,0,consensus,1.0,2,233
+ABplpaapppa,neuron,0,exact,1.0,1,10
+ABplpaapppaa,neuron,0,ancestor,1.0,1,1
+ABplpaapppap,neuron,0,ancestor,1.0,1,1
+ABplpaapppapa,neuron,0,ancestor,1.0,1,1
+ABplpaapppapp,neuron,0,ancestor,1.0,1,1
+ABplpaapppp,neuron,0,consensus,1.0,1,10
+ABplpaappppa,neuron,0,exact,1.0,1,1
+ABplpaappppp,neuron,0,ancestor,1.0,1,1
+ABplpaapppppa,neuron,0,ancestor,1.0,1,1
+ABplpaapppppp,neuron,0,ancestor,1.0,1,1
+ABplpap,mixed,11,consensus,0.357,14,258
+ABplpapa,mixed,11,consensus,0.375,8,258
+ABplpapaa,mixed,11,consensus,0.5,4,257
+ABplpapaaa,neuron,0,consensus,1.0,2,233
+ABplpapaaaa,neuron,0,exact,1.0,1,3
+ABplpapaaap,neuron,0,exact,1.0,1,3
+ABplpapaap,other,10,consensus,1.0,2,233
+ABplpapaapa,other,10,exact,1.0,1,3
+ABplpapaapp,other,10,exact,1.0,1,3
+ABplpapaappa,other,10,ancestor,1.0,1,1
+ABplpapaappaa,other,10,ancestor,1.0,1,1
+ABplpapaappap,other,10,ancestor,1.0,1,1
+ABplpapaappp,other,10,ancestor,1.0,1,1
+ABplpapaapppa,other,10,ancestor,1.0,1,1
+ABplpapaapppp,other,10,ancestor,1.0,1,1
+ABplpapaappppa,other,10,ancestor,1.0,1,1
+ABplpapaappppaa,other,10,ancestor,1.0,1,1
+ABplpapaappppap,other,10,ancestor,1.0,1,1
+ABplpapaappppp,other,10,ancestor,1.0,1,1
+ABplpapaapppppa,other,10,ancestor,1.0,1,1
+ABplpapaapppppp,other,10,ancestor,1.0,1,1
+ABplpapap,mixed,11,consensus,0.25,4,257
+ABplpapapa,mixed,11,consensus,0.5,2,233
+ABplpapapaa,excretory,7,exact,1.0,1,6
+ABplpapapap,neuron,0,exact,1.0,1,6
+ABplpapapapa,neuron,0,ancestor,1.0,1,1
+ABplpapapapp,neuron,0,ancestor,1.0,1,1
+ABplpapapappa,neuron,0,ancestor,1.0,1,1
+ABplpapapappp,neuron,0,ancestor,1.0,1,1
+ABplpapapp,mixed,11,consensus,0.5,2,233
+ABplpapappa,other,10,exact,1.0,1,5
+ABplpapappaa,other,10,ancestor,1.0,1,1
+ABplpapappaaa,other,10,ancestor,1.0,1,1
+ABplpapappaaaa,other,10,ancestor,1.0,1,1
+ABplpapappaaap,other,10,ancestor,1.0,1,1
+ABplpapappaap,other,10,ancestor,1.0,1,1
+ABplpapappap,other,10,ancestor,1.0,1,1
+ABplpapappp,muscle,1,exact,1.0,1,5
+ABplpapp,mixed,11,consensus,0.333,6,258
+ABplpappa,mixed,11,consensus,0.5,2,257
+ABplpappaa,mixed,11,consensus,0.5,2,236
+ABplpappaaa,neuron,0,exact,1.0,1,28
+ABplpappaap,excretory,7,exact,1.0,1,28
+ABplpappaapa,excretory,7,ancestor,1.0,1,2
+ABplpappaapaa,excretory,7,ancestor,1.0,1,1
+ABplpappaapaaa,excretory,7,ancestor,1.0,1,1
+ABplpappaapaap,excretory,7,ancestor,1.0,1,1
+ABplpappaapaapa,excretory,7,ancestor,1.0,1,1
+ABplpappaapaapp,excretory,7,ancestor,1.0,1,1
+ABplpappaapap,excretory,7,ancestor,1.0,1,1
+ABplpappaapp,excretory,7,ancestor,1.0,1,2
+ABplpappap,mixed,11,ancestor,0.5,2,236
+ABplpappapa,mixed,11,ancestor,0.5,2,2
+ABplpappapaa,mixed,11,ancestor,0.5,2,1
+ABplpappapap,mixed,11,ancestor,0.5,2,1
+ABplpappapapa,mixed,11,ancestor,0.5,2,1
+ABplpappapapp,mixed,11,ancestor,0.5,2,1
+ABplpappapappa,mixed,11,ancestor,0.5,2,1
+ABplpappapappp,mixed,11,ancestor,0.5,2,1
+ABplpappapp,mixed,11,ancestor,0.5,2,2
+ABplpappp,mixed,11,consensus,0.5,4,257
+ABplpapppa,other,10,consensus,1.0,2,231
+ABplpapppaa,other,10,exact,1.0,1,3
+ABplpapppap,other,10,exact,1.0,1,3
+ABplpapppp,mixed,11,consensus,0.5,2,231
+ABplpappppa,neuron,0,exact,1.0,1,2
+ABplpappppp,intestine,4,exact,1.0,1,2
+ABplpapppppa,intestine,4,ancestor,1.0,1,1
+ABplpapppppp,intestine,4,ancestor,1.0,1,1
+ABplpp,mixed,11,consensus,0.414,29,260
+ABplppa,mixed,11,consensus,0.571,14,260
+ABplppaa,neuron,0,consensus,0.6,5,260
+ABplppaaa,mixed,11,consensus,0.5,2,258
+ABplppaaaa,mixed,11,consensus,0.5,2,234
+ABplppaaaaa,other,10,exact,1.0,1,4
+ABplppaaaap,neuron,0,consensus,1.0,1,4
+ABplppaaaapa,neuron,0,ancestor,1.0,1,1
+ABplppaaaapp,neuron,0,exact,1.0,1,1
+ABplppaaaappa,neuron,0,ancestor,1.0,1,1
+ABplppaaaappp,neuron,0,ancestor,1.0,1,1
+ABplppaaaapppa,neuron,0,ancestor,1.0,1,1
+ABplppaaaapppaa,neuron,0,ancestor,1.0,1,1
+ABplppaaaapppap,neuron,0,ancestor,1.0,1,1
+ABplppaaaapppp,neuron,0,ancestor,1.0,1,1
+ABplppaaaappppa,neuron,0,ancestor,1.0,1,1
+ABplppaaaappppp,neuron,0,ancestor,1.0,1,1
+ABplppaaap,mixed,11,ancestor,0.5,2,234
+ABplppaaapa,mixed,11,ancestor,0.5,2,1
+ABplppaaapaa,mixed,11,ancestor,0.5,2,1
+ABplppaaapap,mixed,11,ancestor,0.5,2,1
+ABplppaaapp,mixed,11,ancestor,0.5,2,1
+ABplppaap,neuron,0,consensus,0.667,3,258
+ABplppaapa,neuron,0,consensus,1.0,1,234
+ABplppaapaa,neuron,0,ancestor,1.0,1,3
+ABplppaapap,neuron,0,exact,1.0,1,3
+ABplppaapp,mixed,11,consensus,0.5,2,234
+ABplppaappa,neuron,0,exact,1.0,1,4
+ABplppaappaa,neuron,0,ancestor,1.0,1,1
+ABplppaappap,neuron,0,ancestor,1.0,1,1
+ABplppaappp,muscle,1,exact,1.0,1,4
+ABplppaapppa,muscle,1,ancestor,1.0,1,1
+ABplppaapppp,muscle,1,ancestor,1.0,1,1
+ABplppap,mixed,11,consensus,0.556,9,260
+ABplppapa,muscle,1,consensus,0.8,5,259
+ABplppapaa,muscle,1,consensus,0.667,3,235
+ABplppapaaa,mixed,11,consensus,0.5,2,3
+ABplppapaaaa,muscle,1,exact,1.0,1,1
+ABplppapaaaaa,muscle,1,ancestor,1.0,1,1
+ABplppapaaaap,muscle,1,ancestor,1.0,1,1
+ABplppapaaaapa,muscle,1,ancestor,1.0,1,1
+ABplppapaaaapaa,muscle,1,ancestor,1.0,1,1
+ABplppapaaaapap,muscle,1,ancestor,1.0,1,1
+ABplppapaaaapp,muscle,1,ancestor,1.0,1,1
+ABplppapaaap,neuron,0,exact,1.0,1,1
+ABplppapaap,muscle,1,exact,1.0,1,3
+ABplppapap,muscle,1,consensus,1.0,2,235
+ABplppapapa,muscle,1,exact,1.0,1,4
+ABplppapapaa,muscle,1,ancestor,1.0,1,1
+ABplppapapaaa,muscle,1,ancestor,1.0,1,1
+ABplppapapaaaa,muscle,1,ancestor,1.0,1,1
+ABplppapapaaap,muscle,1,ancestor,1.0,1,1
+ABplppapapaap,muscle,1,ancestor,1.0,1,1
+ABplppapapap,muscle,1,ancestor,1.0,1,1
+ABplppapapp,muscle,1,exact,1.0,1,4
+ABplppapp,neuron,0,consensus,1.0,4,259
+ABplppappa,neuron,0,consensus,1.0,2,235
+ABplppappaa,neuron,0,exact,1.0,1,4
+ABplppappaaa,neuron,0,ancestor,1.0,1,1
+ABplppappaap,neuron,0,ancestor,1.0,1,1
+ABplppappap,neuron,0,exact,1.0,1,4
+ABplppappapa,neuron,0,ancestor,1.0,1,2
+ABplppappapaa,neuron,0,ancestor,1.0,1,2
+ABplppappapap,neuron,0,ancestor,1.0,1,2
+ABplppappapapa,neuron,0,ancestor,1.0,1,1
+ABplppappapapp,neuron,0,ancestor,1.0,1,1
+ABplppappapp,neuron,0,ancestor,1.0,1,2
+ABplppappp,neuron,0,consensus,1.0,2,235
+ABplppapppa,neuron,0,exact,1.0,1,4
+ABplppapppaa,neuron,0,ancestor,1.0,1,1
+ABplppapppaaa,neuron,0,ancestor,1.0,1,1
+ABplppapppaap,neuron,0,ancestor,1.0,1,1
+ABplppapppaapa,neuron,0,ancestor,1.0,1,1
+ABplppapppaapaa,neuron,0,ancestor,1.0,1,1
+ABplppapppaapaaa,neuron,0,ancestor,1.0,1,1
+ABplppapppaapaap,neuron,0,ancestor,1.0,1,1
+ABplppapppaapap,neuron,0,ancestor,1.0,1,1
+ABplppapppaapp,neuron,0,ancestor,1.0,1,1
+ABplppapppaappa,neuron,0,ancestor,1.0,1,1
+ABplppapppaappp,neuron,0,ancestor,1.0,1,1
+ABplppapppap,neuron,0,ancestor,1.0,1,1
+ABplppapppp,neuron,0,exact,1.0,1,4
+ABplppappppa,neuron,0,ancestor,1.0,1,1
+ABplppappppaa,neuron,0,ancestor,1.0,1,1
+ABplppappppap,neuron,0,ancestor,1.0,1,1
+ABplppappppp,neuron,0,ancestor,1.0,1,1
+ABplppapppppa,neuron,0,ancestor,1.0,1,1
+ABplppapppppp,neuron,0,ancestor,1.0,1,1
+ABplppp,mixed,11,consensus,0.267,15,260
+ABplpppa,mixed,11,consensus,0.429,7,260
+ABplpppaa,neuron,0,consensus,0.6,5,259
+ABplpppaaa,muscle,1,consensus,1.0,2,234
+ABplpppaaaa,muscle,1,exact,1.0,1,3
+ABplpppaaap,muscle,1,exact,1.0,1,3
+ABplpppaap,neuron,0,consensus,1.0,3,234
+ABplpppaapa,neuron,0,consensus,1.0,2,5
+ABplpppaapp,neuron,0,exact,1.0,1,5
+ABplpppap,mixed,11,consensus,0.5,2,259
+ABplpppapa,mixed,11,consensus,0.5,2,234
+ABplpppapaa,glia,5,exact,1.0,1,13
+ABplpppapaaa,glia,5,ancestor,1.0,1,1
+ABplpppapaaaa,glia,5,ancestor,1.0,1,1
+ABplpppapaaap,glia,5,ancestor,1.0,1,1
+ABplpppapaap,glia,5,ancestor,1.0,1,1
+ABplpppapap,hypodermis,2,exact,1.0,1,13
+ABplpppapp,mixed,11,ancestor,0.5,2,234
+ABplpppappa,mixed,11,ancestor,0.5,2,3
+ABplpppappaa,mixed,11,ancestor,0.5,2,1
+ABplpppappap,mixed,11,ancestor,0.5,2,1
+ABplpppappp,mixed,11,ancestor,0.5,2,3
+ABplpppapppa,mixed,11,ancestor,0.5,2,1
+ABplpppapppaa,mixed,11,ancestor,0.5,2,1
+ABplpppapppaaa,mixed,11,ancestor,0.5,2,1
+ABplpppapppaaaa,mixed,11,ancestor,0.5,2,1
+ABplpppapppaaaaa,mixed,11,ancestor,0.5,2,1
+ABplpppapppaaaaaa,mixed,11,ancestor,0.5,2,1
+ABplpppapppaaaaap,mixed,11,ancestor,0.5,2,1
+ABplpppapppaaaap,mixed,11,ancestor,0.5,2,1
+ABplpppapppaaap,mixed,11,ancestor,0.5,2,1
+ABplpppapppaap,mixed,11,ancestor,0.5,2,1
+ABplpppapppap,mixed,11,ancestor,0.5,2,1
+ABplpppapppp,mixed,11,ancestor,0.5,2,1
+ABplpppappppa,mixed,11,ancestor,0.5,2,1
+ABplpppappppaa,mixed,11,ancestor,0.5,2,1
+ABplpppappppap,mixed,11,ancestor,0.5,2,1
+ABplpppappppapa,mixed,11,ancestor,0.5,2,1
+ABplpppappppapp,mixed,11,ancestor,0.5,2,1
+ABplpppappppp,mixed,11,ancestor,0.5,2,1
+ABplpppapppppa,mixed,11,ancestor,0.5,2,1
+ABplpppapppppp,mixed,11,ancestor,0.5,2,1
+ABplpppp,mixed,11,consensus,0.25,8,260
+ABplppppa,mixed,11,consensus,0.5,4,259
+ABplppppaa,mixed,11,consensus,0.5,2,235
+ABplppppaaa,neuron,0,exact,1.0,1,9
+ABplppppaap,intestine,4,exact,1.0,1,9
+ABplppppap,other,10,consensus,1.0,2,235
+ABplppppapa,other,10,exact,1.0,1,8
+ABplppppapp,other,10,exact,1.0,1,8
+ABplppppp,mixed,11,consensus,0.5,4,259
+ABplpppppa,mixed,11,consensus,0.5,2,235
+ABplpppppaa,intestine,4,exact,1.0,1,7
+ABplpppppap,muscle,1,exact,1.0,1,7
+ABplpppppp,hypodermis,2,consensus,1.0,2,235
+ABplppppppa,hypodermis,2,exact,1.0,1,11
+ABplppppppaa,hypodermis,2,ancestor,1.0,1,1
+ABplppppppap,hypodermis,2,ancestor,1.0,1,1
+ABplppppppp,hypodermis,2,exact,1.0,1,11
+ABplpppppppa,hypodermis,2,ancestor,1.0,1,1
+ABplpppppppp,hypodermis,2,ancestor,1.0,1,1
+ABpr,mixed,11,consensus,0.486,107,260
+ABpra,mixed,11,consensus,0.447,47,260
+ABpraa,mixed,11,consensus,0.52,25,260
+ABpraaa,neuron,0,consensus,0.692,13,259
+ABpraaaa,mixed,11,consensus,0.5,6,258
+ABpraaaaa,glia,5,consensus,0.667,3,256
+ABpraaaaaa,mixed,11,consensus,0.5,2,233
+ABpraaaaaaa,neuron,0,exact,1.0,1,1
+ABpraaaaaap,glia,5,exact,1.0,1,1
+ABpraaaaap,glia,5,consensus,1.0,1,233
+ABpraaaaapd,glia,5,exact,1.0,1,2
+ABpraaaaapv,glia,5,ancestor,1.0,1,2
+ABpraaaaapva,glia,5,ancestor,1.0,1,1
+ABpraaaaapvp,glia,5,ancestor,1.0,1,1
+ABpraaaaapvpa,glia,5,ancestor,1.0,1,1
+ABpraaaaapvpp,glia,5,ancestor,1.0,1,1
+ABpraaaap,neuron,0,consensus,0.667,3,256
+ABpraaaapa,mixed,11,consensus,0.5,2,233
+ABpraaaapad,neuron,0,exact,1.0,1,3
+ABpraaaapav,glia,5,exact,1.0,1,3
+ABpraaaapp,neuron,0,consensus,1.0,1,233
+ABpraaaappa,neuron,0,ancestor,1.0,1,4
+ABpraaaappp,neuron,0,consensus,1.0,1,4
+ABpraaaapppa,neuron,0,exact,1.0,1,2
+ABpraaaapppaa,neuron,0,ancestor,1.0,1,1
+ABpraaaapppap,neuron,0,ancestor,1.0,1,1
+ABpraaaapppp,neuron,0,ancestor,1.0,1,2
+ABpraaaappppa,neuron,0,ancestor,1.0,1,2
+ABpraaaappppaa,neuron,0,ancestor,1.0,1,2
+ABpraaaappppap,neuron,0,ancestor,1.0,1,2
+ABpraaaappppp,neuron,0,ancestor,1.0,1,2
+ABpraaaapppppa,neuron,0,ancestor,1.0,1,2
+ABpraaaapppppaa,neuron,0,ancestor,1.0,1,1
+ABpraaaapppppaaa,neuron,0,ancestor,1.0,1,1
+ABpraaaapppppaap,neuron,0,ancestor,1.0,1,1
+ABpraaaapppppap,neuron,0,ancestor,1.0,1,1
+ABpraaaapppppp,neuron,0,ancestor,1.0,1,2
+ABpraaap,neuron,0,consensus,0.857,7,258
+ABpraaapa,neuron,0,consensus,1.0,2,257
+ABpraaapaa,neuron,0,consensus,1.0,1,233
+ABpraaapaad,neuron,0,exact,1.0,1,2
+ABpraaapaada,neuron,0,ancestor,1.0,1,1
+ABpraaapaadp,neuron,0,ancestor,1.0,1,1
+ABpraaapaav,neuron,0,ancestor,1.0,1,2
+ABpraaapaava,neuron,0,ancestor,1.0,1,2
+ABpraaapaavp,neuron,0,ancestor,1.0,1,2
+ABpraaapaavpa,neuron,0,ancestor,1.0,1,1
+ABpraaapaavpp,neuron,0,ancestor,1.0,1,1
+ABpraaapaavppa,neuron,0,ancestor,1.0,1,1
+ABpraaapaavppaa,neuron,0,ancestor,1.0,1,1
+ABpraaapaavppap,neuron,0,ancestor,1.0,1,1
+ABpraaapaavppp,neuron,0,ancestor,1.0,1,1
+ABpraaapap,neuron,0,consensus,1.0,1,233
+ABpraaapapa,neuron,0,consensus,1.0,1,1
+ABpraaapapaa,neuron,0,exact,1.0,1,1
+ABpraaapapap,neuron,0,ancestor,1.0,1,1
+ABpraaapapp,neuron,0,ancestor,1.0,1,1
+ABpraaapappa,neuron,0,ancestor,1.0,1,1
+ABpraaapappaa,neuron,0,ancestor,1.0,1,1
+ABpraaapappap,neuron,0,ancestor,1.0,1,1
+ABpraaapappapa,neuron,0,ancestor,1.0,1,1
+ABpraaapappapp,neuron,0,ancestor,1.0,1,1
+ABpraaapappp,neuron,0,ancestor,1.0,1,1
+ABpraaapapppa,neuron,0,ancestor,1.0,1,1
+ABpraaapapppaa,neuron,0,ancestor,1.0,1,1
+ABpraaapapppaaa,neuron,0,ancestor,1.0,1,1
+ABpraaapapppaaaa,neuron,0,ancestor,1.0,1,1
+ABpraaapapppaaap,neuron,0,ancestor,1.0,1,1
+ABpraaapapppaap,neuron,0,ancestor,1.0,1,1
+ABpraaapapppap,neuron,0,ancestor,1.0,1,1
+ABpraaapapppapa,neuron,0,ancestor,1.0,1,1
+ABpraaapapppapaa,neuron,0,ancestor,1.0,1,1
+ABpraaapapppapap,neuron,0,ancestor,1.0,1,1
+ABpraaapapppapp,neuron,0,ancestor,1.0,1,1
+ABpraaapapppappa,neuron,0,ancestor,1.0,1,1
+ABpraaapapppappp,neuron,0,ancestor,1.0,1,1
+ABpraaapapppp,neuron,0,ancestor,1.0,1,1
+ABpraaapp,neuron,0,consensus,0.8,5,257
+ABpraaappa,mixed,11,consensus,0.5,2,234
+ABpraaappaa,neuron,0,exact,1.0,1,3
+ABpraaappap,glia,5,exact,1.0,1,3
+ABpraaappapa,glia,5,ancestor,1.0,1,1
+ABpraaappapaa,glia,5,ancestor,1.0,1,1
+ABpraaappapap,glia,5,ancestor,1.0,1,1
+ABpraaappapapa,glia,5,ancestor,1.0,1,1
+ABpraaappapapp,glia,5,ancestor,1.0,1,1
+ABpraaappapp,glia,5,ancestor,1.0,1,1
+ABpraaappappa,glia,5,ancestor,1.0,1,1
+ABpraaappappp,glia,5,ancestor,1.0,1,1
+ABpraaappp,neuron,0,consensus,1.0,3,234
+ABpraaapppa,neuron,0,consensus,1.0,1,31
+ABpraaapppp,neuron,0,consensus,1.0,2,31
+ABpraaappppa,neuron,0,exact,1.0,1,1
+ABpraaappppaa,neuron,0,ancestor,1.0,1,1
+ABpraaappppaaa,neuron,0,ancestor,1.0,1,1
+ABpraaappppaaaa,neuron,0,ancestor,1.0,1,1
+ABpraaappppaaap,neuron,0,ancestor,1.0,1,1
+ABpraaappppaap,neuron,0,ancestor,1.0,1,1
+ABpraaappppap,neuron,0,ancestor,1.0,1,1
+ABpraaappppp,neuron,0,exact,1.0,1,1
+ABpraap,mixed,11,consensus,0.417,12,259
+ABpraapa,mixed,11,consensus,0.5,8,258
+ABpraapaa,mixed,11,consensus,0.5,4,257
+ABpraapaaa,mixed,11,consensus,0.5,2,232
+ABpraapaaaa,hypodermis,2,exact,1.0,1,1
+ABpraapaaaaa,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaaa,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaaaa,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaaaaa,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaaaaaa,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaaaaap,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaaaap,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaaap,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaaapa,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaaapp,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaap,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaapa,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaapaa,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaapap,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaaapp,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaap,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaapa,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaaapp,hypodermis,2,ancestor,1.0,1,1
+ABpraapaaap,glia,5,exact,1.0,1,1
+ABpraapaap,mixed,11,consensus,0.5,2,232
+ABpraapap,neuron,0,consensus,0.75,4,257
+ABpraapapa,mixed,11,consensus,0.5,2,232
+ABpraapapp,neuron,0,consensus,1.0,2,232
+ABpraapappa,neuron,0,exact,1.0,1,3
+ABpraapappp,neuron,0,consensus,1.0,1,3
+ABpraapp,hypodermis,2,consensus,1.0,4,258
+ABpraappa,hypodermis,2,consensus,1.0,2,257
+ABpraappaa,hypodermis,2,exact,1.0,1,233
+ABpraappaaa,hypodermis,2,ancestor,1.0,1,1
+ABpraappaap,hypodermis,2,ancestor,1.0,1,1
+ABpraappaapa,hypodermis,2,ancestor,1.0,1,1
+ABpraappaapp,hypodermis,2,ancestor,1.0,1,1
+ABpraappap,hypodermis,2,exact,1.0,1,233
+ABpraappp,hypodermis,2,consensus,1.0,2,257
+ABpraapppa,hypodermis,2,exact,1.0,1,233
+ABpraapppaa,hypodermis,2,ancestor,1.0,1,1
+ABpraapppap,hypodermis,2,ancestor,1.0,1,1
+ABpraapppp,hypodermis,2,exact,1.0,1,233
+ABprap,mixed,11,consensus,0.409,22,260
+ABprapa,mixed,11,consensus,0.462,13,260
+ABprapaa,neuron,0,consensus,0.714,7,260
+ABprapaaa,neuron,0,consensus,1.0,5,258
+ABprapaaaa,neuron,0,consensus,1.0,2,235
+ABprapaaaaa,neuron,0,ancestor,1.0,2,3
+ABprapaaaap,neuron,0,consensus,1.0,2,3
+ABprapaaap,neuron,0,consensus,1.0,3,235
+ABprapaaapa,neuron,0,consensus,1.0,2,5
+ABprapaaapp,neuron,0,exact,1.0,1,5
+ABprapaap,mixed,11,consensus,0.5,2,258
+ABprapaapa,other,10,exact,1.0,1,236
+ABprapaapp,hypodermis,2,exact,1.0,1,236
+ABprapap,mixed,11,consensus,0.5,6,260
+ABprapapa,hypodermis,2,consensus,0.667,3,259
+ABprapapaa,mixed,11,consensus,0.5,2,237
+ABprapapap,hypodermis,2,exact,1.0,1,237
+ABprapapapa,hypodermis,2,ancestor,1.0,1,1
+ABprapapapp,hypodermis,2,ancestor,1.0,1,1
+ABprapapappa,hypodermis,2,ancestor,1.0,1,1
+ABprapapappaa,hypodermis,2,ancestor,1.0,1,1
+ABprapapappap,hypodermis,2,ancestor,1.0,1,1
+ABprapapappp,hypodermis,2,ancestor,1.0,1,1
+ABprapapp,mixed,11,consensus,0.333,3,259
+ABprapappa,hypodermis,2,exact,1.0,1,237
+ABprapappp,mixed,11,consensus,0.5,2,237
+ABprapapppa,mixed,11,ancestor,0.5,2,4
+ABprapapppp,mixed,11,consensus,0.5,2,4
+ABprapp,mixed,11,consensus,0.556,9,260
+ABprappa,hypodermis,2,consensus,1.0,4,260
+ABprappaa,hypodermis,2,consensus,1.0,2,259
+ABprappaaa,hypodermis,2,exact,1.0,1,236
+ABprappaap,hypodermis,2,exact,1.0,1,236
+ABprappap,hypodermis,2,consensus,1.0,2,259
+ABprappapa,hypodermis,2,exact,1.0,1,237
+ABprappapp,hypodermis,2,exact,1.0,1,237
+ABprappp,mixed,11,consensus,0.4,5,260
+ABprapppa,neuron,0,consensus,0.667,3,259
+ABprapppaa,neuron,0,consensus,1.0,1,236
+ABprapppaaa,neuron,0,exact,1.0,1,2
+ABprapppaap,neuron,0,ancestor,1.0,1,2
+ABprapppaapa,neuron,0,ancestor,1.0,1,1
+ABprapppaapaa,neuron,0,ancestor,1.0,1,1
+ABprapppaapap,neuron,0,ancestor,1.0,1,1
+ABprapppaapp,neuron,0,ancestor,1.0,1,1
+ABprapppap,mixed,11,consensus,0.5,2,236
+ABprapppapa,mixed,11,ancestor,0.5,2,3
+ABprapppapp,mixed,11,consensus,0.5,2,3
+ABprapppp,mixed,11,consensus,0.5,2,259
+ABprappppa,hypodermis,2,exact,1.0,1,236
+ABprappppaa,hypodermis,2,ancestor,1.0,1,1
+ABprappppap,hypodermis,2,ancestor,1.0,1,1
+ABprappppp,glia,5,exact,1.0,1,236
+ABprapppppa,glia,5,ancestor,1.0,1,2
+ABprapppppaa,glia,5,ancestor,1.0,1,1
+ABprapppppap,glia,5,ancestor,1.0,1,1
+ABprapppppp,glia,5,ancestor,1.0,1,2
+ABprappppppa,glia,5,ancestor,1.0,1,1
+ABprappppppaa,glia,5,ancestor,1.0,1,1
+ABprappppppap,glia,5,ancestor,1.0,1,1
+ABprappppppp,glia,5,ancestor,1.0,1,1
+ABprapppppppa,glia,5,ancestor,1.0,1,1
+ABprapppppppp,glia,5,ancestor,1.0,1,1
+ABprp,mixed,11,consensus,0.517,60,260
+ABprpa,mixed,11,consensus,0.562,32,260
+ABprpaa,neuron,0,consensus,0.625,16,259
+ABprpaaa,mixed,11,consensus,0.5,8,259
+ABprpaaaa,mixed,11,consensus,0.5,4,258
+ABprpaaaaa,mixed,11,consensus,0.5,2,234
+ABprpaaaaaa,neuron,0,exact,1.0,1,5
+ABprpaaaaaaa,neuron,0,ancestor,1.0,1,3
+ABprpaaaaaap,neuron,0,ancestor,1.0,1,3
+ABprpaaaaap,glia,5,exact,1.0,1,5
+ABprpaaaaapa,glia,5,ancestor,1.0,1,2
+ABprpaaaaapaa,glia,5,ancestor,1.0,1,1
+ABprpaaaaapaaa,glia,5,ancestor,1.0,1,1
+ABprpaaaaapaap,glia,5,ancestor,1.0,1,1
+ABprpaaaaapap,glia,5,ancestor,1.0,1,1
+ABprpaaaaapapa,glia,5,ancestor,1.0,1,1
+ABprpaaaaapapp,glia,5,ancestor,1.0,1,1
+ABprpaaaaapp,glia,5,ancestor,1.0,1,2
+ABprpaaaaappa,glia,5,ancestor,1.0,1,1
+ABprpaaaaappp,glia,5,ancestor,1.0,1,1
+ABprpaaaap,mixed,11,consensus,0.5,2,234
+ABprpaaaapa,glia,5,exact,1.0,1,7
+ABprpaaaapaa,glia,5,ancestor,1.0,1,1
+ABprpaaaapaaa,glia,5,ancestor,1.0,1,1
+ABprpaaaapaap,glia,5,ancestor,1.0,1,1
+ABprpaaaapap,glia,5,ancestor,1.0,1,1
+ABprpaaaapapa,glia,5,ancestor,1.0,1,1
+ABprpaaaapapp,glia,5,ancestor,1.0,1,1
+ABprpaaaapappa,glia,5,ancestor,1.0,1,1
+ABprpaaaapappp,glia,5,ancestor,1.0,1,1
+ABprpaaaapp,muscle,1,exact,1.0,1,7
+ABprpaaap,neuron,0,consensus,0.75,4,258
+ABprpaaapa,mixed,11,consensus,0.5,2,234
+ABprpaaapaa,neuron,0,exact,1.0,1,2
+ABprpaaapaaa,neuron,0,ancestor,1.0,1,1
+ABprpaaapaap,neuron,0,ancestor,1.0,1,1
+ABprpaaapap,glia,5,exact,1.0,1,2
+ABprpaaapapa,glia,5,ancestor,1.0,1,1
+ABprpaaapapaa,glia,5,ancestor,1.0,1,1
+ABprpaaapapap,glia,5,ancestor,1.0,1,1
+ABprpaaapapp,glia,5,ancestor,1.0,1,1
+ABprpaaapappa,glia,5,ancestor,1.0,1,1
+ABprpaaapappp,glia,5,ancestor,1.0,1,1
+ABprpaaapapppa,glia,5,ancestor,1.0,1,1
+ABprpaaapapppp,glia,5,ancestor,1.0,1,1
+ABprpaaapappppa,glia,5,ancestor,1.0,1,1
+ABprpaaapappppp,glia,5,ancestor,1.0,1,1
+ABprpaaapp,neuron,0,consensus,1.0,2,234
+ABprpaaappa,neuron,0,consensus,1.0,1,3
+ABprpaaappp,neuron,0,exact,1.0,1,3
+ABprpaaapppa,neuron,0,ancestor,1.0,1,1
+ABprpaaapppp,neuron,0,ancestor,1.0,1,1
+ABprpaap,neuron,0,consensus,0.75,8,259
+ABprpaapa,mixed,11,consensus,0.5,4,257
+ABprpaapaa,neuron,0,consensus,1.0,2,233
+ABprpaapaaa,neuron,0,exact,1.0,1,2
+ABprpaapaaaa,neuron,0,ancestor,1.0,1,1
+ABprpaapaaap,neuron,0,ancestor,1.0,1,1
+ABprpaapaaapa,neuron,0,ancestor,1.0,1,1
+ABprpaapaaapp,neuron,0,ancestor,1.0,1,1
+ABprpaapaap,neuron,0,exact,1.0,1,2
+ABprpaapaapa,neuron,0,ancestor,1.0,1,1
+ABprpaapaapp,neuron,0,ancestor,1.0,1,1
+ABprpaapap,mixed,11,consensus,0.5,2,233
+ABprpaapapa,glia,5,exact,1.0,1,2
+ABprpaapapaa,glia,5,ancestor,1.0,1,1
+ABprpaapapap,glia,5,ancestor,1.0,1,1
+ABprpaapapp,death,9,exact,1.0,1,2
+ABprpaapappa,death,9,ancestor,1.0,1,1
+ABprpaapappaa,death,9,ancestor,1.0,1,1
+ABprpaapappap,death,9,ancestor,1.0,1,1
+ABprpaapappp,death,9,ancestor,1.0,1,1
+ABprpaapp,neuron,0,consensus,1.0,4,257
+ABprpaappa,neuron,0,consensus,1.0,2,233
+ABprpaappaa,neuron,0,exact,1.0,1,4
+ABprpaappaaa,neuron,0,ancestor,1.0,1,1
+ABprpaappaap,neuron,0,ancestor,1.0,1,1
+ABprpaappap,neuron,0,exact,1.0,1,4
+ABprpaappp,neuron,0,consensus,1.0,2,233
+ABprpaapppa,neuron,0,exact,1.0,1,3
+ABprpaapppp,neuron,0,consensus,1.0,1,3
+ABprpaappppa,neuron,0,exact,1.0,1,1
+ABprpaappppaa,neuron,0,ancestor,1.0,1,1
+ABprpaappppap,neuron,0,ancestor,1.0,1,1
+ABprpaappppp,neuron,0,ancestor,1.0,1,1
+ABprpap,mixed,11,consensus,0.5,16,259
+ABprpapa,mixed,11,consensus,0.375,8,258
+ABprpapaa,mixed,11,consensus,0.5,4,257
+ABprpapaaa,neuron,0,consensus,1.0,2,233
+ABprpapaaaa,neuron,0,exact,1.0,1,4
+ABprpapaaap,neuron,0,exact,1.0,1,4
+ABprpapaaapa,neuron,0,ancestor,1.0,1,1
+ABprpapaaapp,neuron,0,ancestor,1.0,1,1
+ABprpapaap,other,10,consensus,1.0,2,233
+ABprpapaapa,other,10,exact,1.0,1,5
+ABprpapaapaa,other,10,ancestor,1.0,1,1
+ABprpapaapaaa,other,10,ancestor,1.0,1,1
+ABprpapaapaap,other,10,ancestor,1.0,1,1
+ABprpapaapap,other,10,ancestor,1.0,1,1
+ABprpapaapapa,other,10,ancestor,1.0,1,1
+ABprpapaapapaa,other,10,ancestor,1.0,1,1
+ABprpapaapapaaa,other,10,ancestor,1.0,1,1
+ABprpapaapapaap,other,10,ancestor,1.0,1,1
+ABprpapaapapap,other,10,ancestor,1.0,1,1
+ABprpapaapapapa,other,10,ancestor,1.0,1,1
+ABprpapaapapapaa,other,10,ancestor,1.0,1,1
+ABprpapaapapapap,other,10,ancestor,1.0,1,1
+ABprpapaapapapp,other,10,ancestor,1.0,1,1
+ABprpapaapapp,other,10,ancestor,1.0,1,1
+ABprpapaapp,other,10,exact,1.0,1,5
+ABprpapaappa,other,10,ancestor,1.0,1,1
+ABprpapaappp,other,10,ancestor,1.0,1,1
+ABprpapaapppa,other,10,ancestor,1.0,1,1
+ABprpapaapppaa,other,10,ancestor,1.0,1,1
+ABprpapaapppaaa,other,10,ancestor,1.0,1,1
+ABprpapaapppaap,other,10,ancestor,1.0,1,1
+ABprpapaapppaapa,other,10,ancestor,1.0,1,1
+ABprpapaapppaapp,other,10,ancestor,1.0,1,1
+ABprpapaapppap,other,10,ancestor,1.0,1,1
+ABprpapaapppapa,other,10,ancestor,1.0,1,1
+ABprpapaapppapp,other,10,ancestor,1.0,1,1
+ABprpapaapppappa,other,10,ancestor,1.0,1,1
+ABprpapaapppappaa,other,10,ancestor,1.0,1,1
+ABprpapaapppappap,other,10,ancestor,1.0,1,1
+ABprpapaapppappp,other,10,ancestor,1.0,1,1
+ABprpapaapppp,other,10,ancestor,1.0,1,1
+ABprpapap,mixed,11,consensus,0.25,4,257
+ABprpapapa,mixed,11,consensus,0.5,2,233
+ABprpapapaa,excretory,7,exact,1.0,1,4
+ABprpapapap,neuron,0,exact,1.0,1,4
+ABprpapapp,mixed,11,consensus,0.5,2,233
+ABprpapappa,other,10,exact,1.0,1,5
+ABprpapappaa,other,10,ancestor,1.0,1,1
+ABprpapappap,other,10,ancestor,1.0,1,1
+ABprpapappp,muscle,1,exact,1.0,1,5
+ABprpapapppa,muscle,1,ancestor,1.0,1,1
+ABprpapapppp,muscle,1,ancestor,1.0,1,1
+ABprpapappppa,muscle,1,ancestor,1.0,1,1
+ABprpapappppp,muscle,1,ancestor,1.0,1,1
+ABprpapp,neuron,0,consensus,0.625,8,258
+ABprpappa,neuron,0,consensus,0.75,4,257
+ABprpappaa,neuron,0,consensus,1.0,2,232
+ABprpappaaa,neuron,0,exact,1.0,1,11
+ABprpappaap,neuron,0,exact,1.0,1,11
+ABprpappap,mixed,11,consensus,0.5,2,232
+ABprpappapa,neuron,0,exact,1.0,1,6
+ABprpappapp,muscle,1,exact,1.0,1,6
+ABprpappp,mixed,11,consensus,0.5,4,257
+ABprpapppa,neuron,0,consensus,1.0,2,232
+ABprpapppaa,neuron,0,exact,1.0,1,5
+ABprpapppap,neuron,0,exact,1.0,1,5
+ABprpapppapa,neuron,0,ancestor,1.0,1,1
+ABprpapppapaa,neuron,0,ancestor,1.0,1,1
+ABprpapppapaaa,neuron,0,ancestor,1.0,1,1
+ABprpapppapaap,neuron,0,ancestor,1.0,1,1
+ABprpapppapap,neuron,0,ancestor,1.0,1,1
+ABprpapppapapa,neuron,0,ancestor,1.0,1,1
+ABprpapppapapp,neuron,0,ancestor,1.0,1,1
+ABprpapppapp,neuron,0,ancestor,1.0,1,1
+ABprpapppappa,neuron,0,ancestor,1.0,1,1
+ABprpapppappp,neuron,0,ancestor,1.0,1,1
+ABprpapppapppa,neuron,0,ancestor,1.0,1,1
+ABprpapppapppp,neuron,0,ancestor,1.0,1,1
+ABprpapppp,intestine,4,consensus,1.0,2,232
+ABprpappppa,intestine,4,exact,1.0,1,5
+ABprpappppaa,intestine,4,ancestor,1.0,1,1
+ABprpappppap,intestine,4,ancestor,1.0,1,1
+ABprpappppp,intestine,4,exact,1.0,1,5
+ABprpapppppa,intestine,4,ancestor,1.0,1,2
+ABprpapppppp,intestine,4,ancestor,1.0,1,2
+ABprpp,mixed,11,consensus,0.464,28,260
+ABprppa,mixed,11,consensus,0.571,14,260
+ABprppaa,neuron,0,consensus,0.6,5,260
+ABprppaaa,mixed,11,consensus,0.5,2,258
+ABprppaaaa,mixed,11,consensus,0.5,2,233
+ABprppaaaaa,other,10,exact,1.0,1,1
+ABprppaaaap,neuron,0,consensus,1.0,1,1
+ABprppaaap,mixed,11,ancestor,0.5,2,233
+ABprppaaapa,mixed,11,ancestor,0.5,2,1
+ABprppaaapp,mixed,11,ancestor,0.5,2,1
+ABprppaap,neuron,0,consensus,0.667,3,258
+ABprppaapa,neuron,0,consensus,1.0,1,234
+ABprppaapaa,neuron,0,ancestor,1.0,1,2
+ABprppaapaaa,neuron,0,ancestor,1.0,1,1
+ABprppaapaap,neuron,0,ancestor,1.0,1,1
+ABprppaapaapa,neuron,0,ancestor,1.0,1,1
+ABprppaapaapp,neuron,0,ancestor,1.0,1,1
+ABprppaapaappa,neuron,0,ancestor,1.0,1,1
+ABprppaapaappaa,neuron,0,ancestor,1.0,1,1
+ABprppaapaappap,neuron,0,ancestor,1.0,1,1
+ABprppaapaappp,neuron,0,ancestor,1.0,1,1
+ABprppaapap,neuron,0,exact,1.0,1,2
+ABprppaapapa,neuron,0,ancestor,1.0,1,1
+ABprppaapapp,neuron,0,ancestor,1.0,1,1
+ABprppaapp,mixed,11,consensus,0.5,2,234
+ABprppaappa,neuron,0,exact,1.0,1,2
+ABprppaappaa,neuron,0,ancestor,1.0,1,1
+ABprppaappap,neuron,0,ancestor,1.0,1,1
+ABprppaappp,muscle,1,exact,1.0,1,2
+ABprppap,mixed,11,consensus,0.556,9,260
+ABprppapa,muscle,1,consensus,0.8,5,258
+ABprppapaa,muscle,1,consensus,0.667,3,235
+ABprppapaaa,mixed,11,consensus,0.5,2,5
+ABprppapaap,muscle,1,exact,1.0,1,5
+ABprppapaapa,muscle,1,ancestor,1.0,1,1
+ABprppapaapp,muscle,1,ancestor,1.0,1,1
+ABprppapap,muscle,1,consensus,1.0,2,235
+ABprppapapa,muscle,1,exact,1.0,1,1
+ABprppapapp,muscle,1,exact,1.0,1,1
+ABprppapp,neuron,0,consensus,1.0,4,258
+ABprppappa,neuron,0,consensus,1.0,2,235
+ABprppappaa,neuron,0,exact,1.0,1,1
+ABprppappap,neuron,0,exact,1.0,1,1
+ABprppappp,neuron,0,consensus,1.0,2,235
+ABprppapppa,neuron,0,exact,1.0,1,2
+ABprppapppaa,neuron,0,ancestor,1.0,1,1
+ABprppapppap,neuron,0,ancestor,1.0,1,1
+ABprppapppapa,neuron,0,ancestor,1.0,1,1
+ABprppapppapp,neuron,0,ancestor,1.0,1,1
+ABprppapppappa,neuron,0,ancestor,1.0,1,1
+ABprppapppappp,neuron,0,ancestor,1.0,1,1
+ABprppapppp,neuron,0,exact,1.0,1,2
+ABprppp,mixed,11,consensus,0.357,14,260
+ABprpppa,mixed,11,consensus,0.429,7,260
+ABprpppaa,neuron,0,consensus,0.6,5,259
+ABprpppaaa,mixed,11,consensus,0.5,2,235
+ABprpppaaaa,other,10,exact,1.0,1,3
+ABprpppaaaaa,other,10,ancestor,1.0,1,1
+ABprpppaaaap,other,10,ancestor,1.0,1,1
+ABprpppaaaapa,other,10,ancestor,1.0,1,1
+ABprpppaaaapp,other,10,ancestor,1.0,1,1
+ABprpppaaap,muscle,1,exact,1.0,1,3
+ABprpppaaapa,muscle,1,ancestor,1.0,1,2
+ABprpppaaapp,muscle,1,ancestor,1.0,1,2
+ABprpppaaappa,muscle,1,ancestor,1.0,1,1
+ABprpppaaappp,muscle,1,ancestor,1.0,1,1
+ABprpppaap,neuron,0,consensus,1.0,3,235
+ABprpppaapa,neuron,0,consensus,1.0,2,1
+ABprpppaapp,neuron,0,exact,1.0,1,1
+ABprpppaappa,neuron,0,ancestor,1.0,1,1
+ABprpppaappaa,neuron,0,ancestor,1.0,1,1
+ABprpppaappap,neuron,0,ancestor,1.0,1,1
+ABprpppaappp,neuron,0,ancestor,1.0,1,1
+ABprpppap,mixed,11,consensus,0.5,2,259
+ABprpppapa,mixed,11,consensus,0.5,2,235
+ABprpppapaa,glia,5,exact,1.0,1,9
+ABprpppapap,hypodermis,2,exact,1.0,1,9
+ABprpppapp,mixed,11,ancestor,0.5,2,235
+ABprpppappa,mixed,11,ancestor,0.5,2,3
+ABprpppappaa,mixed,11,ancestor,0.5,2,1
+ABprpppappap,mixed,11,ancestor,0.5,2,1
+ABprpppappp,mixed,11,ancestor,0.5,2,3
+ABprpppp,mixed,11,consensus,0.286,7,260
+ABprppppa,mixed,11,consensus,0.5,4,259
+ABprppppaa,mixed,11,consensus,0.5,2,235
+ABprppppaaa,neuron,0,exact,1.0,1,4
+ABprppppaap,intestine,4,exact,1.0,1,4
+ABprppppap,mixed,11,consensus,0.5,2,235
+ABprppppapa,other,10,exact,1.0,1,7
+ABprppppapp,neuron,0,exact,1.0,1,7
+ABprppppappa,neuron,0,ancestor,1.0,1,1
+ABprppppappaa,neuron,0,ancestor,1.0,1,1
+ABprppppappaaa,neuron,0,ancestor,1.0,1,1
+ABprppppappaap,neuron,0,ancestor,1.0,1,1
+ABprppppappap,neuron,0,ancestor,1.0,1,1
+ABprppppappp,neuron,0,ancestor,1.0,1,1
+ABprppppp,mixed,11,consensus,0.333,3,259
+ABprpppppa,mixed,11,consensus,0.5,2,234
+ABprpppppaa,muscle,1,exact,1.0,1,5
+ABprpppppap,intestine,4,exact,1.0,1,5
+ABprpppppp,hypodermis,2,consensus,1.0,1,234
+ABprppppppa,hypodermis,2,ancestor,1.0,1,8
+ABprppppppp,hypodermis,2,exact,1.0,1,8
+ABprpppppppa,hypodermis,2,ancestor,1.0,1,1
+ABprpppppppp,hypodermis,2,ancestor,1.0,1,1
+C,muscle,1,consensus,0.681,47,260
+Ca,muscle,1,consensus,0.696,23,260
+Caa,hypodermis,2,consensus,0.714,7,259
+Caaa,hypodermis,2,consensus,1.0,4,259
+Caaaa,hypodermis,2,consensus,1.0,2,258
+Caaaaa,hypodermis,2,exact,1.0,1,241
+Caaaaaa,hypodermis,2,ancestor,1.0,1,1
+Caaaaap,hypodermis,2,ancestor,1.0,1,1
+Caaaap,hypodermis,2,exact,1.0,1,241
+Caaap,hypodermis,2,consensus,1.0,2,258
+Caaapa,hypodermis,2,exact,1.0,1,241
+Caaapp,hypodermis,2,exact,1.0,1,241
+Caap,neuron,0,consensus,0.667,3,259
+Caapa,neuron,0,consensus,1.0,1,258
+Caapaa,neuron,0,exact,1.0,1,12
+Caapap,neuron,0,ancestor,1.0,1,12
+Caapapa,neuron,0,ancestor,1.0,1,1
+Caapapp,neuron,0,ancestor,1.0,1,1
+Caapp,mixed,11,consensus,0.5,2,258
+Caappd,hypodermis,2,exact,1.0,1,236
+Caappv,neuron,0,exact,1.0,1,236
+Cap,muscle,1,consensus,1.0,16,259
+Capa,muscle,1,consensus,1.0,8,259
+Capaa,muscle,1,consensus,1.0,4,254
+Capaaa,muscle,1,consensus,1.0,2,210
+Capaaaa,muscle,1,exact,1.0,1,8
+Capaaap,muscle,1,exact,1.0,1,8
+Capaaapa,muscle,1,ancestor,1.0,1,1
+Capaaapp,muscle,1,ancestor,1.0,1,1
+Capaap,muscle,1,consensus,1.0,2,210
+Capaapa,muscle,1,exact,1.0,1,8
+Capaapaa,muscle,1,ancestor,1.0,1,1
+Capaapaaa,muscle,1,ancestor,1.0,1,1
+Capaapaap,muscle,1,ancestor,1.0,1,1
+Capaapaapa,muscle,1,ancestor,1.0,1,1
+Capaapaapp,muscle,1,ancestor,1.0,1,1
+Capaapap,muscle,1,ancestor,1.0,1,1
+Capaapp,muscle,1,exact,1.0,1,8
+Capap,muscle,1,consensus,1.0,4,254
+Capapa,muscle,1,consensus,1.0,2,202
+Capapaa,muscle,1,exact,1.0,1,8
+Capapap,muscle,1,exact,1.0,1,8
+Capapp,muscle,1,consensus,1.0,2,202
+Capappa,muscle,1,exact,1.0,1,7
+Capappp,muscle,1,exact,1.0,1,7
+Capp,muscle,1,consensus,1.0,8,259
+Cappa,muscle,1,consensus,1.0,4,258
+Cappaa,muscle,1,consensus,1.0,2,235
+Cappaaa,muscle,1,exact,1.0,1,9
+Cappaaaa,muscle,1,ancestor,1.0,1,1
+Cappaaap,muscle,1,ancestor,1.0,1,1
+Cappaap,muscle,1,exact,1.0,1,9
+Cappap,muscle,1,consensus,1.0,2,235
+Cappapa,muscle,1,exact,1.0,1,8
+Cappapp,muscle,1,exact,1.0,1,8
+Cappappa,muscle,1,ancestor,1.0,1,1
+Cappappp,muscle,1,ancestor,1.0,1,1
+Cappp,muscle,1,consensus,1.0,4,258
+Capppa,muscle,1,consensus,1.0,2,232
+Capppaa,muscle,1,exact,1.0,1,8
+Capppap,muscle,1,exact,1.0,1,8
+Capppp,muscle,1,consensus,1.0,2,232
+Cappppd,muscle,1,exact,1.0,1,7
+Cappppv,muscle,1,exact,1.0,1,7
+Cp,muscle,1,consensus,0.667,24,260
+Cpa,hypodermis,2,consensus,1.0,8,259
+Cpaa,hypodermis,2,consensus,1.0,4,259
+Cpaaa,hypodermis,2,consensus,1.0,2,258
+Cpaaaa,hypodermis,2,exact,1.0,1,241
+Cpaaaaa,hypodermis,2,ancestor,1.0,1,1
+Cpaaaap,hypodermis,2,ancestor,1.0,1,1
+Cpaaap,hypodermis,2,exact,1.0,1,241
+Cpaaapa,hypodermis,2,ancestor,1.0,1,1
+Cpaaapp,hypodermis,2,ancestor,1.0,1,1
+Cpaap,hypodermis,2,consensus,1.0,2,258
+Cpaapa,hypodermis,2,exact,1.0,1,242
+Cpaapp,hypodermis,2,exact,1.0,1,242
+Cpap,hypodermis,2,consensus,1.0,4,259
+Cpapa,hypodermis,2,consensus,1.0,2,258
+Cpapaa,hypodermis,2,exact,1.0,1,239
+Cpapaaa,hypodermis,2,ancestor,1.0,1,1
+Cpapaap,hypodermis,2,ancestor,1.0,1,1
+Cpapap,hypodermis,2,exact,1.0,1,239
+Cpapp,hypodermis,2,consensus,1.0,2,258
+Cpappd,hypodermis,2,exact,1.0,1,239
+Cpappv,hypodermis,2,exact,1.0,1,239
+Cpp,muscle,1,consensus,1.0,16,259
+Cppa,muscle,1,consensus,1.0,8,259
+Cppaa,muscle,1,consensus,1.0,4,257
+Cppaaa,muscle,1,consensus,1.0,2,219
+Cppaaaa,muscle,1,exact,1.0,1,8
+Cppaaap,muscle,1,exact,1.0,1,8
+Cppaap,muscle,1,consensus,1.0,2,219
+Cppaapa,muscle,1,exact,1.0,1,7
+Cppaapp,muscle,1,exact,1.0,1,7
+Cppap,muscle,1,consensus,1.0,4,257
+Cppapa,muscle,1,consensus,1.0,2,212
+Cppapaa,muscle,1,exact,1.0,1,8
+Cppapap,muscle,1,exact,1.0,1,8
+Cppapp,muscle,1,consensus,1.0,2,212
+Cppappa,muscle,1,exact,1.0,1,7
+Cppappaa,muscle,1,ancestor,1.0,1,1
+Cppappap,muscle,1,ancestor,1.0,1,1
+Cppappp,muscle,1,exact,1.0,1,7
+Cppp,muscle,1,consensus,1.0,8,259
+Cpppa,muscle,1,consensus,1.0,4,258
+Cpppaa,muscle,1,consensus,1.0,2,239
+Cpppaaa,muscle,1,exact,1.0,1,9
+Cpppaaaa,muscle,1,ancestor,1.0,1,1
+Cpppaaap,muscle,1,ancestor,1.0,1,1
+Cpppaap,muscle,1,exact,1.0,1,9
+Cpppap,muscle,1,consensus,1.0,2,239
+Cpppapa,muscle,1,exact,1.0,1,9
+Cpppapaa,muscle,1,ancestor,1.0,1,1
+Cpppapap,muscle,1,ancestor,1.0,1,1
+Cpppapp,muscle,1,exact,1.0,1,9
+Cpppp,muscle,1,consensus,1.0,4,258
+Cppppa,muscle,1,consensus,1.0,2,234
+Cppppaa,muscle,1,exact,1.0,1,9
+Cppppap,muscle,1,exact,1.0,1,9
+Cppppp,muscle,1,consensus,1.0,2,234
+Cpppppd,muscle,1,exact,1.0,1,8
+Cpppppv,muscle,1,exact,1.0,1,8
+D,muscle,1,consensus,1.0,19,258
+Da,muscle,1,consensus,1.0,10,258
+Daa,muscle,1,consensus,1.0,4,257
+Daaa,muscle,1,consensus,1.0,2,236
+Daaaa,muscle,1,exact,1.0,1,25
+Daaaaa,muscle,1,ancestor,1.0,1,2
+Daaaap,muscle,1,ancestor,1.0,1,2
+Daaap,muscle,1,exact,1.0,1,25
+Daaapa,muscle,1,ancestor,1.0,1,1
+Daaapp,muscle,1,ancestor,1.0,1,1
+Daap,muscle,1,consensus,1.0,2,236
+Daapa,muscle,1,exact,1.0,1,21
+Daapaa,muscle,1,ancestor,1.0,1,1
+Daapap,muscle,1,ancestor,1.0,1,1
+Daapp,muscle,1,exact,1.0,1,21
+Daappa,muscle,1,ancestor,1.0,1,1
+Daappp,muscle,1,ancestor,1.0,1,1
+Dap,muscle,1,consensus,1.0,6,257
+Dapa,muscle,1,consensus,1.0,2,241
+Dapaa,muscle,1,exact,1.0,1,35
+Dapap,muscle,1,exact,1.0,1,35
+Dapp,muscle,1,consensus,1.0,4,241
+Dappa,muscle,1,consensus,1.0,2,47
+Dappaa,muscle,1,exact,1.0,1,3
+Dappap,muscle,1,exact,1.0,1,3
+Dappapa,muscle,1,ancestor,1.0,1,1
+Dappapp,muscle,1,ancestor,1.0,1,1
+Dappp,muscle,1,consensus,1.0,2,47
+Dapppa,muscle,1,exact,1.0,1,2
+Dapppp,muscle,1,exact,1.0,1,2
+Dp,muscle,1,consensus,1.0,9,258
+Dpa,muscle,1,consensus,1.0,3,257
+Dpaa,muscle,1,consensus,1.0,2,234
+Dpaaa,muscle,1,exact,1.0,1,18
+Dpaaaa,muscle,1,ancestor,1.0,1,1
+Dpaaap,muscle,1,ancestor,1.0,1,1
+Dpaaapa,muscle,1,ancestor,1.0,1,1
+Dpaaapp,muscle,1,ancestor,1.0,1,1
+Dpaap,muscle,1,exact,1.0,1,18
+Dpap,muscle,1,consensus,1.0,1,234
+Dpapa,muscle,1,exact,1.0,1,21
+Dpapp,muscle,1,ancestor,1.0,1,21
+Dpappa,muscle,1,ancestor,1.0,1,1
+Dpappaa,muscle,1,ancestor,1.0,1,1
+Dpappap,muscle,1,ancestor,1.0,1,1
+Dpappp,muscle,1,ancestor,1.0,1,1
+Dpapppa,muscle,1,ancestor,1.0,1,1
+Dpapppp,muscle,1,ancestor,1.0,1,1
+Dpp,muscle,1,consensus,1.0,6,257
+Dppa,muscle,1,consensus,1.0,2,238
+Dppaa,muscle,1,exact,1.0,1,29
+Dppaaa,muscle,1,ancestor,1.0,1,1
+Dppaap,muscle,1,ancestor,1.0,1,1
+Dppaapa,muscle,1,ancestor,1.0,1,1
+Dppaapp,muscle,1,ancestor,1.0,1,1
+Dppap,muscle,1,exact,1.0,1,29
+Dppp,muscle,1,consensus,1.0,4,238
+Dpppa,muscle,1,consensus,1.0,2,43
+Dpppaa,muscle,1,exact,1.0,1,3
+Dpppap,muscle,1,exact,1.0,1,3
+Dpppapa,muscle,1,ancestor,1.0,1,1
+Dpppapp,muscle,1,ancestor,1.0,1,1
+Dpppappa,muscle,1,ancestor,1.0,1,1
+Dpppappp,muscle,1,ancestor,1.0,1,1
+Dpppp,muscle,1,consensus,1.0,2,43
+Dppppa,muscle,1,exact,1.0,1,1
+Dppppp,muscle,1,exact,1.0,1,1
+E,intestine,4,consensus,1.0,20,260
+EMS,mixed,11,founder,1.0,0,253
+Ea,intestine,4,consensus,1.0,10,260
+Eal,intestine,4,consensus,1.0,5,260
+Eala,intestine,4,consensus,1.0,3,260
+Ealaa,intestine,4,consensus,1.0,2,235
+Ealaad,intestine,4,exact,1.0,1,1
+Ealaada,intestine,4,ancestor,1.0,1,1
+Ealaadaa,intestine,4,ancestor,1.0,1,1
+Ealaadap,intestine,4,ancestor,1.0,1,1
+Ealaadp,intestine,4,ancestor,1.0,1,1
+Ealaav,intestine,4,exact,1.0,1,1
+Ealaava,intestine,4,ancestor,1.0,1,1
+Ealaavaa,intestine,4,ancestor,1.0,1,1
+Ealaavap,intestine,4,ancestor,1.0,1,1
+Ealaavapa,intestine,4,ancestor,1.0,1,1
+Ealaavapp,intestine,4,ancestor,1.0,1,1
+Ealaavp,intestine,4,ancestor,1.0,1,1
+Ealaavpa,intestine,4,ancestor,1.0,1,1
+Ealaavpp,intestine,4,ancestor,1.0,1,1
+Ealap,intestine,4,exact,1.0,1,235
+Ealapa,intestine,4,ancestor,1.0,1,1
+Ealapaa,intestine,4,ancestor,1.0,1,1
+Ealapap,intestine,4,ancestor,1.0,1,1
+Ealapp,intestine,4,ancestor,1.0,1,1
+Ealp,intestine,4,consensus,1.0,2,260
+Ealpa,intestine,4,exact,1.0,1,235
+Ealpp,intestine,4,exact,1.0,1,235
+Ealppa,intestine,4,ancestor,1.0,1,1
+Ealppp,intestine,4,ancestor,1.0,1,1
+Ear,intestine,4,consensus,1.0,5,260
+Eara,intestine,4,consensus,1.0,3,260
+Earaa,intestine,4,consensus,1.0,2,232
+Earap,intestine,4,exact,1.0,1,232
+Earp,intestine,4,consensus,1.0,2,260
+Earpa,intestine,4,exact,1.0,1,232
+Earpp,intestine,4,exact,1.0,1,232
+Ep,intestine,4,consensus,1.0,10,260
+Epl,intestine,4,consensus,1.0,5,260
+Epla,intestine,4,consensus,1.0,2,260
+Eplaa,intestine,4,exact,1.0,1,233
+Eplaaa,intestine,4,ancestor,1.0,1,1
+Eplaaaa,intestine,4,ancestor,1.0,1,1
+Eplaaap,intestine,4,ancestor,1.0,1,1
+Eplaap,intestine,4,ancestor,1.0,1,1
+Eplaapa,intestine,4,ancestor,1.0,1,1
+Eplaapp,intestine,4,ancestor,1.0,1,1
+Eplaappa,intestine,4,ancestor,1.0,1,1
+Eplaappp,intestine,4,ancestor,1.0,1,1
+Eplap,intestine,4,exact,1.0,1,233
+Eplp,intestine,4,consensus,1.0,3,260
+Eplpa,intestine,4,exact,1.0,1,223
+Eplpp,intestine,4,consensus,1.0,2,223
+Eplppa,intestine,4,exact,1.0,1,1
+Eplppp,intestine,4,exact,1.0,1,1
+Epr,intestine,4,consensus,1.0,5,260
+Epra,intestine,4,consensus,1.0,2,260
+Epraa,intestine,4,exact,1.0,1,232
+Eprap,intestine,4,exact,1.0,1,232
+Eprp,intestine,4,consensus,1.0,3,260
+Eprpa,intestine,4,exact,1.0,1,218
+Eprpaa,intestine,4,ancestor,1.0,1,1
+Eprpaaa,intestine,4,ancestor,1.0,1,1
+Eprpaap,intestine,4,ancestor,1.0,1,1
+Eprpaapa,intestine,4,ancestor,1.0,1,1
+Eprpaapaa,intestine,4,ancestor,1.0,1,1
+Eprpaapap,intestine,4,ancestor,1.0,1,1
+Eprpaapp,intestine,4,ancestor,1.0,1,1
+Eprpap,intestine,4,ancestor,1.0,1,1
+Eprpapa,intestine,4,ancestor,1.0,1,1
+Eprpapaa,intestine,4,ancestor,1.0,1,1
+Eprpapaaa,intestine,4,ancestor,1.0,1,1
+Eprpapaap,intestine,4,ancestor,1.0,1,1
+Eprpapap,intestine,4,ancestor,1.0,1,1
+Eprpapp,intestine,4,ancestor,1.0,1,1
+Eprpp,intestine,4,consensus,1.0,2,218
+MS,mixed,11,founder,1.0,0,260
+MSa,mixed,11,consensus,0.476,42,258
+MSaa,pharynx,3,consensus,0.692,26,258
+MSaaa,pharynx,3,consensus,0.923,13,258
+MSaaaa,pharynx,3,consensus,1.0,8,258
+MSaaaaa,pharynx,3,consensus,1.0,5,256
+MSaaaaaa,pharynx,3,consensus,1.0,2,235
+MSaaaaaal,pharynx,3,exact,1.0,1,2
+MSaaaaaala,pharynx,3,ancestor,1.0,1,1
+MSaaaaaalp,pharynx,3,ancestor,1.0,1,1
+MSaaaaaar,pharynx,3,exact,1.0,1,2
+MSaaaaap,pharynx,3,consensus,1.0,3,235
+MSaaaaapa,pharynx,3,consensus,1.0,2,18
+MSaaaaapp,pharynx,3,exact,1.0,1,18
+MSaaaap,pharynx,3,consensus,1.0,3,256
+MSaaaapa,pharynx,3,consensus,1.0,2,232
+MSaaaapaa,pharynx,3,exact,1.0,1,3
+MSaaaapap,pharynx,3,exact,1.0,1,3
+MSaaaapp,pharynx,3,consensus,1.0,1,232
+MSaaaappa,pharynx,3,ancestor,1.0,1,2
+MSaaaappp,pharynx,3,exact,1.0,1,2
+MSaaap,pharynx,3,consensus,0.8,5,258
+MSaaapa,pharynx,3,consensus,1.0,4,256
+MSaaapaa,pharynx,3,consensus,1.0,2,233
+MSaaapaaa,pharynx,3,exact,1.0,1,5
+MSaaapaap,pharynx,3,exact,1.0,1,5
+MSaaapap,pharynx,3,consensus,1.0,2,233
+MSaaapapa,pharynx,3,exact,1.0,1,7
+MSaaapapp,pharynx,3,exact,1.0,1,7
+MSaaapappa,pharynx,3,ancestor,1.0,1,1
+MSaaapappaa,pharynx,3,ancestor,1.0,1,1
+MSaaapappap,pharynx,3,ancestor,1.0,1,1
+MSaaapappp,pharynx,3,ancestor,1.0,1,1
+MSaaapp,intestine,4,consensus,1.0,1,256
+MSaaappa,intestine,4,ancestor,1.0,1,88
+MSaaappp,intestine,4,exact,1.0,1,88
+MSaaapppa,intestine,4,ancestor,1.0,1,1
+MSaaapppp,intestine,4,ancestor,1.0,1,1
+MSaaappppa,intestine,4,ancestor,1.0,1,1
+MSaaappppaa,intestine,4,ancestor,1.0,1,1
+MSaaappppaaa,intestine,4,ancestor,1.0,1,1
+MSaaappppaaaa,intestine,4,ancestor,1.0,1,1
+MSaaappppaaap,intestine,4,ancestor,1.0,1,1
+MSaaappppaaapa,intestine,4,ancestor,1.0,1,1
+MSaaappppaaapp,intestine,4,ancestor,1.0,1,1
+MSaaappppaap,intestine,4,ancestor,1.0,1,1
+MSaaappppap,intestine,4,ancestor,1.0,1,1
+MSaaappppp,intestine,4,ancestor,1.0,1,1
+MSaap,mixed,11,consensus,0.462,13,258
+MSaapa,pharynx,3,consensus,0.857,7,258
+MSaapaa,pharynx,3,consensus,1.0,4,256
+MSaapaaa,pharynx,3,consensus,1.0,2,233
+MSaapaaaa,pharynx,3,exact,1.0,1,6
+MSaapaaaaa,pharynx,3,ancestor,1.0,1,1
+MSaapaaaaaa,pharynx,3,ancestor,1.0,1,1
+MSaapaaaaaaa,pharynx,3,ancestor,1.0,1,1
+MSaapaaaaaap,pharynx,3,ancestor,1.0,1,1
+MSaapaaaaap,pharynx,3,ancestor,1.0,1,1
+MSaapaaaaapa,pharynx,3,ancestor,1.0,1,1
+MSaapaaaaapp,pharynx,3,ancestor,1.0,1,1
+MSaapaaaap,pharynx,3,ancestor,1.0,1,1
+MSaapaaap,pharynx,3,exact,1.0,1,6
+MSaapaaapa,pharynx,3,ancestor,1.0,1,1
+MSaapaaapaa,pharynx,3,ancestor,1.0,1,1
+MSaapaaapaaa,pharynx,3,ancestor,1.0,1,1
+MSaapaaapaap,pharynx,3,ancestor,1.0,1,1
+MSaapaaapap,pharynx,3,ancestor,1.0,1,1
+MSaapaaapp,pharynx,3,ancestor,1.0,1,1
+MSaapaaappa,pharynx,3,ancestor,1.0,1,1
+MSaapaaappp,pharynx,3,ancestor,1.0,1,1
+MSaapaap,pharynx,3,consensus,1.0,2,233
+MSaapaapa,pharynx,3,consensus,1.0,1,12
+MSaapaapp,pharynx,3,exact,1.0,1,12
+MSaapaappa,pharynx,3,ancestor,1.0,1,1
+MSaapaappp,pharynx,3,ancestor,1.0,1,1
+MSaapaapppa,pharynx,3,ancestor,1.0,1,1
+MSaapaapppp,pharynx,3,ancestor,1.0,1,1
+MSaapap,pharynx,3,consensus,0.667,3,256
+MSaapapa,pharynx,3,consensus,1.0,1,232
+MSaapapaa,pharynx,3,exact,1.0,1,2
+MSaapapaaa,pharynx,3,ancestor,1.0,1,1
+MSaapapaaaa,pharynx,3,ancestor,1.0,1,1
+MSaapapaaap,pharynx,3,ancestor,1.0,1,1
+MSaapapaap,pharynx,3,ancestor,1.0,1,1
+MSaapapaapa,pharynx,3,ancestor,1.0,1,1
+MSaapapaapp,pharynx,3,ancestor,1.0,1,1
+MSaapapaappa,pharynx,3,ancestor,1.0,1,1
+MSaapapaappp,pharynx,3,ancestor,1.0,1,1
+MSaapapap,pharynx,3,ancestor,1.0,1,2
+MSaapapapa,pharynx,3,ancestor,1.0,1,1
+MSaapapapaa,pharynx,3,ancestor,1.0,1,1
+MSaapapapap,pharynx,3,ancestor,1.0,1,1
+MSaapapapp,pharynx,3,ancestor,1.0,1,1
+MSaapapappa,pharynx,3,ancestor,1.0,1,1
+MSaapapappp,pharynx,3,ancestor,1.0,1,1
+MSaapapapppa,pharynx,3,ancestor,1.0,1,1
+MSaapapapppp,pharynx,3,ancestor,1.0,1,1
+MSaapapp,mixed,11,consensus,0.5,2,232
+MSaapappa,pharynx,3,exact,1.0,1,3
+MSaapappp,intestine,4,exact,1.0,1,3
+MSaapapppa,intestine,4,ancestor,1.0,1,1
+MSaapapppp,intestine,4,ancestor,1.0,1,1
+MSaapappppa,intestine,4,ancestor,1.0,1,1
+MSaapappppp,intestine,4,ancestor,1.0,1,1
+MSaapp,muscle,1,consensus,0.667,6,258
+MSaappa,intestine,4,consensus,1.0,2,252
+MSaappaa,intestine,4,exact,1.0,1,17
+MSaappap,intestine,4,exact,1.0,1,17
+MSaappp,muscle,1,consensus,1.0,4,252
+MSaapppa,muscle,1,consensus,1.0,2,46
+MSaapppp,muscle,1,consensus,1.0,2,46
+MSaappppa,muscle,1,exact,1.0,1,1
+MSaappppp,muscle,1,exact,1.0,1,1
+MSap,mixed,11,consensus,0.562,16,258
+MSapa,mixed,11,consensus,0.444,9,258
+MSapaa,mixed,11,consensus,0.5,4,258
+MSapaaa,pharynx,3,consensus,0.667,3,254
+MSapaaaa,pharynx,3,consensus,1.0,2,225
+MSapaaap,muscle,1,exact,1.0,1,225
+MSapaap,other,10,exact,1.0,1,254
+MSapaapa,other,10,ancestor,1.0,1,80
+MSapaapaa,other,10,ancestor,1.0,1,1
+MSapaapaaa,other,10,ancestor,1.0,1,1
+MSapaapaap,other,10,ancestor,1.0,1,1
+MSapaapaapa,other,10,ancestor,1.0,1,1
+MSapaapaapp,other,10,ancestor,1.0,1,1
+MSapaapap,other,10,ancestor,1.0,1,1
+MSapaapapa,other,10,ancestor,1.0,1,1
+MSapaapapp,other,10,ancestor,1.0,1,1
+MSapaapappa,other,10,ancestor,1.0,1,1
+MSapaapappaa,other,10,ancestor,1.0,1,1
+MSapaapappap,other,10,ancestor,1.0,1,1
+MSapaapappp,other,10,ancestor,1.0,1,1
+MSapaapapppa,other,10,ancestor,1.0,1,1
+MSapaapapppp,other,10,ancestor,1.0,1,1
+MSapaapp,other,10,ancestor,1.0,1,80
+MSapaappa,other,10,ancestor,1.0,1,1
+MSapaappaa,other,10,ancestor,1.0,1,1
+MSapaappaaa,other,10,ancestor,1.0,1,1
+MSapaappaaaa,other,10,ancestor,1.0,1,1
+MSapaappaaap,other,10,ancestor,1.0,1,1
+MSapaappaaapa,other,10,ancestor,1.0,1,1
+MSapaappaaapp,other,10,ancestor,1.0,1,1
+MSapaappaaappa,other,10,ancestor,1.0,1,1
+MSapaappaaappp,other,10,ancestor,1.0,1,1
+MSapaappaap,other,10,ancestor,1.0,1,1
+MSapaappaapa,other,10,ancestor,1.0,1,1
+MSapaappaapp,other,10,ancestor,1.0,1,1
+MSapaappap,other,10,ancestor,1.0,1,1
+MSapaappp,other,10,ancestor,1.0,1,1
+MSapap,muscle,1,consensus,0.6,5,258
+MSapapa,coelomocyte,8,consensus,0.667,3,251
+MSapapaa,coelomocyte,8,consensus,1.0,2,225
+MSapapap,muscle,1,exact,1.0,1,225
+MSapapp,muscle,1,consensus,1.0,2,251
+MSapappa,muscle,1,exact,1.0,1,166
+MSapappaa,muscle,1,ancestor,1.0,1,1
+MSapappaaa,muscle,1,ancestor,1.0,1,1
+MSapappaap,muscle,1,ancestor,1.0,1,1
+MSapappap,muscle,1,ancestor,1.0,1,1
+MSapappp,muscle,1,exact,1.0,1,166
+MSapapppa,muscle,1,ancestor,1.0,1,1
+MSapapppaa,muscle,1,ancestor,1.0,1,1
+MSapapppap,muscle,1,ancestor,1.0,1,1
+MSapapppp,muscle,1,ancestor,1.0,1,1
+MSapp,muscle,1,consensus,0.714,7,258
+MSappa,mixed,11,consensus,0.333,3,258
+MSappaa,mixed,11,consensus,0.5,2,249
+MSappaaa,other,10,exact,1.0,1,43
+MSappaap,germline,6,exact,1.0,1,43
+MSappap,muscle,1,consensus,1.0,1,249
+MSappapa,muscle,1,ancestor,1.0,1,20
+MSappapp,muscle,1,exact,1.0,1,20
+MSappappa,muscle,1,ancestor,1.0,1,1
+MSappappaa,muscle,1,ancestor,1.0,1,1
+MSappappap,muscle,1,ancestor,1.0,1,1
+MSappappp,muscle,1,ancestor,1.0,1,1
+MSappapppa,muscle,1,ancestor,1.0,1,1
+MSappapppp,muscle,1,ancestor,1.0,1,1
+MSappp,muscle,1,consensus,1.0,4,258
+MSapppa,muscle,1,consensus,1.0,2,247
+MSapppaa,muscle,1,exact,1.0,1,68
+MSapppaaa,muscle,1,ancestor,1.0,1,1
+MSapppaaaa,muscle,1,ancestor,1.0,1,1
+MSapppaaap,muscle,1,ancestor,1.0,1,1
+MSapppaap,muscle,1,ancestor,1.0,1,1
+MSapppaapa,muscle,1,ancestor,1.0,1,1
+MSapppaapaa,muscle,1,ancestor,1.0,1,1
+MSapppaapap,muscle,1,ancestor,1.0,1,1
+MSapppaapp,muscle,1,ancestor,1.0,1,1
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+MSappppa,muscle,1,exact,1.0,1,48
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+MSapppppap,muscle,1,ancestor,1.0,1,1
+MSapppppp,muscle,1,ancestor,1.0,1,1
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+MSpaa,pharynx,3,consensus,0.9,10,258
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+MSpaaaaap,pharynx,3,ancestor,1.0,1,2
+MSpaaaap,pharynx,3,consensus,1.0,2,232
+MSpaaaapa,pharynx,3,exact,1.0,1,12
+MSpaaaapp,pharynx,3,exact,1.0,1,12
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+MSpaaapaap,pharynx,3,ancestor,1.0,1,1
+MSpaaapaapa,pharynx,3,ancestor,1.0,1,1
+MSpaaapaapaa,pharynx,3,ancestor,1.0,1,1
+MSpaaapaapap,pharynx,3,ancestor,1.0,1,1
+MSpaaapaapp,pharynx,3,ancestor,1.0,1,1
+MSpaaapap,pharynx,3,exact,1.0,1,2
+MSpaaapapa,pharynx,3,ancestor,1.0,1,1
+MSpaaapapp,pharynx,3,ancestor,1.0,1,1
+MSpaaapp,pharynx,3,consensus,1.0,2,232
+MSpaaappa,pharynx,3,exact,1.0,1,8
+MSpaaappp,pharynx,3,exact,1.0,1,8
+MSpaap,pharynx,3,consensus,0.667,3,258
+MSpaapa,pharynx,3,consensus,0.667,3,256
+MSpaapaa,pharynx,3,consensus,1.0,1,231
+MSpaapaaa,pharynx,3,exact,1.0,1,2
+MSpaapaaaa,pharynx,3,ancestor,1.0,1,1
+MSpaapaaap,pharynx,3,ancestor,1.0,1,1
+MSpaapaap,pharynx,3,ancestor,1.0,1,2
+MSpaapaapa,pharynx,3,ancestor,1.0,1,1
+MSpaapaapp,pharynx,3,ancestor,1.0,1,1
+MSpaapap,mixed,11,consensus,0.5,2,231
+MSpaapapa,pharynx,3,exact,1.0,1,5
+MSpaapapaa,pharynx,3,ancestor,1.0,1,1
+MSpaapapaaa,pharynx,3,ancestor,1.0,1,1
+MSpaapapaaaa,pharynx,3,ancestor,1.0,1,1
+MSpaapapaaap,pharynx,3,ancestor,1.0,1,1
+MSpaapapaap,pharynx,3,ancestor,1.0,1,1
+MSpaapapap,pharynx,3,ancestor,1.0,1,1
+MSpaapapapa,pharynx,3,ancestor,1.0,1,1
+MSpaapapapp,pharynx,3,ancestor,1.0,1,1
+MSpaapapappa,pharynx,3,ancestor,1.0,1,1
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+MSpaapapappapa,pharynx,3,ancestor,1.0,1,1
+MSpaapapappapp,pharynx,3,ancestor,1.0,1,1
+MSpaapapappp,pharynx,3,ancestor,1.0,1,1
+MSpaapapapppa,pharynx,3,ancestor,1.0,1,1
+MSpaapapapppaa,pharynx,3,ancestor,1.0,1,1
+MSpaapapapppap,pharynx,3,ancestor,1.0,1,1
+MSpaapapapppp,pharynx,3,ancestor,1.0,1,1
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+MSpaappaa,pharynx,3,ancestor,0.667,3,1
+MSpaappaaa,pharynx,3,ancestor,0.667,3,1
+MSpaappaaaa,pharynx,3,ancestor,0.667,3,1
+MSpaappaaap,pharynx,3,ancestor,0.667,3,1
+MSpaappaap,pharynx,3,ancestor,0.667,3,1
+MSpaappap,pharynx,3,ancestor,0.667,3,1
+MSpaappp,pharynx,3,ancestor,0.667,3,1
+MSpap,mixed,11,consensus,0.5,12,258
+MSpapa,pharynx,3,consensus,0.833,6,258
+MSpapaa,pharynx,3,consensus,1.0,3,256
+MSpapaaa,pharynx,3,consensus,1.0,1,231
+MSpapaaaa,pharynx,3,ancestor,1.0,1,7
+MSpapaaaaa,pharynx,3,ancestor,1.0,1,1
+MSpapaaaap,pharynx,3,ancestor,1.0,1,1
+MSpapaaaapa,pharynx,3,ancestor,1.0,1,1
+MSpapaaaapp,pharynx,3,ancestor,1.0,1,1
+MSpapaaaappa,pharynx,3,ancestor,1.0,1,1
+MSpapaaaappp,pharynx,3,ancestor,1.0,1,1
+MSpapaaap,pharynx,3,exact,1.0,1,7
+MSpapaap,pharynx,3,consensus,1.0,2,231
+MSpapaapa,pharynx,3,consensus,1.0,1,14
+MSpapaapaa,pharynx,3,exact,1.0,1,1
+MSpapaapap,pharynx,3,ancestor,1.0,1,1
+MSpapaapapa,pharynx,3,ancestor,1.0,1,1
+MSpapaapapaa,pharynx,3,ancestor,1.0,1,1
+MSpapaapapap,pharynx,3,ancestor,1.0,1,1
+MSpapaapapp,pharynx,3,ancestor,1.0,1,1
+MSpapaapp,pharynx,3,exact,1.0,1,14
+MSpapap,pharynx,3,consensus,0.667,3,256
+MSpapapa,pharynx,3,consensus,1.0,1,232
+MSpapapaa,pharynx,3,exact,1.0,1,1
+MSpapapap,pharynx,3,ancestor,1.0,1,1
+MSpapapp,mixed,11,consensus,0.5,2,232
+MSpapappa,pharynx,3,exact,1.0,1,4
+MSpapappp,intestine,4,exact,1.0,1,4
+MSpapapppa,intestine,4,ancestor,1.0,1,1
+MSpapapppp,intestine,4,ancestor,1.0,1,1
+MSpapp,muscle,1,consensus,1.0,6,258
+MSpappa,muscle,1,consensus,1.0,2,252
+MSpappaa,muscle,1,exact,1.0,1,16
+MSpappaaa,muscle,1,ancestor,1.0,1,1
+MSpappaap,muscle,1,ancestor,1.0,1,1
+MSpappap,muscle,1,exact,1.0,1,16
+MSpappp,muscle,1,consensus,1.0,4,252
+MSpapppa,muscle,1,consensus,1.0,2,94
+MSpapppp,muscle,1,consensus,1.0,2,94
+MSpappppa,muscle,1,exact,1.0,1,1
+MSpappppp,muscle,1,exact,1.0,1,1
+MSpp,muscle,1,consensus,0.6,15,258
+MSppa,mixed,11,consensus,0.444,9,258
+MSppaa,mixed,11,consensus,0.5,4,258
+MSppaaa,pharynx,3,consensus,0.667,3,254
+MSppaaaa,pharynx,3,consensus,1.0,2,226
+MSppaaap,muscle,1,exact,1.0,1,226
+MSppaap,intestine,4,consensus,1.0,1,254
+MSppaapa,intestine,4,ancestor,1.0,1,64
+MSppaapaa,intestine,4,ancestor,1.0,1,1
+MSppaapap,intestine,4,ancestor,1.0,1,1
+MSppaapp,intestine,4,exact,1.0,1,64
+MSppaappa,intestine,4,ancestor,1.0,1,1
+MSppaappaa,intestine,4,ancestor,1.0,1,1
+MSppaappaaa,intestine,4,ancestor,1.0,1,1
+MSppaappaap,intestine,4,ancestor,1.0,1,1
+MSppaappap,intestine,4,ancestor,1.0,1,1
+MSppaappapa,intestine,4,ancestor,1.0,1,1
+MSppaappapp,intestine,4,ancestor,1.0,1,1
+MSppaappp,intestine,4,ancestor,1.0,1,1
+MSppap,muscle,1,consensus,0.6,5,258
+MSppapa,coelomocyte,8,consensus,0.667,3,255
+MSppapaa,coelomocyte,8,consensus,1.0,2,227
+MSppapaaa,coelomocyte,8,exact,1.0,1,1
+MSppapaap,coelomocyte,8,exact,1.0,1,1
+MSppapap,muscle,1,exact,1.0,1,227
+MSppapapa,muscle,1,ancestor,1.0,1,1
+MSppapapp,muscle,1,ancestor,1.0,1,1
+MSppapappa,muscle,1,ancestor,1.0,1,1
+MSppapappp,muscle,1,ancestor,1.0,1,1
+MSppapp,muscle,1,consensus,1.0,2,255
+MSppappa,muscle,1,exact,1.0,1,165
+MSppappaa,muscle,1,ancestor,1.0,1,1
+MSppappaaa,muscle,1,ancestor,1.0,1,1
+MSppappaap,muscle,1,ancestor,1.0,1,1
+MSppappap,muscle,1,ancestor,1.0,1,1
+MSppappp,muscle,1,exact,1.0,1,165
+MSppapppa,muscle,1,ancestor,1.0,1,1
+MSppapppp,muscle,1,ancestor,1.0,1,1
+MSppappppa,muscle,1,ancestor,1.0,1,1
+MSppappppp,muscle,1,ancestor,1.0,1,1
+MSppp,muscle,1,consensus,0.833,6,258
+MSpppa,mixed,11,consensus,0.5,2,258
+MSpppaa,germline,6,consensus,1.0,1,249
+MSpppaaa,germline,6,ancestor,1.0,1,63
+MSpppaaaa,germline,6,ancestor,1.0,1,1
+MSpppaaaaa,germline,6,ancestor,1.0,1,1
+MSpppaaaap,germline,6,ancestor,1.0,1,1
+MSpppaaap,germline,6,ancestor,1.0,1,1
+MSpppaap,germline,6,exact,1.0,1,63
+MSpppap,muscle,1,consensus,1.0,1,249
+MSpppapa,muscle,1,ancestor,1.0,1,31
+MSpppapaa,muscle,1,ancestor,1.0,1,1
+MSpppapaaa,muscle,1,ancestor,1.0,1,1
+MSpppapaap,muscle,1,ancestor,1.0,1,1
+MSpppapap,muscle,1,ancestor,1.0,1,1
+MSpppapapa,muscle,1,ancestor,1.0,1,1
+MSpppapapp,muscle,1,ancestor,1.0,1,1
+MSpppapp,muscle,1,exact,1.0,1,31
+MSpppappa,muscle,1,ancestor,1.0,1,1
+MSpppappaa,muscle,1,ancestor,1.0,1,1
+MSpppappaaa,muscle,1,ancestor,1.0,1,1
+MSpppappaap,muscle,1,ancestor,1.0,1,1
+MSpppappap,muscle,1,ancestor,1.0,1,1
+MSpppappp,muscle,1,ancestor,1.0,1,1
+MSpppp,muscle,1,consensus,1.0,4,258
+MSppppa,muscle,1,consensus,1.0,2,248
+MSppppaa,muscle,1,exact,1.0,1,72
+MSppppap,muscle,1,exact,1.0,1,72
+MSppppapa,muscle,1,ancestor,1.0,1,1
+MSppppapp,muscle,1,ancestor,1.0,1,1
+MSppppp,muscle,1,consensus,1.0,2,248
+MSpppppa,muscle,1,exact,1.0,1,41
+MSpppppaa,muscle,1,ancestor,1.0,1,1
+MSpppppap,muscle,1,ancestor,1.0,1,1
+MSpppppapa,muscle,1,ancestor,1.0,1,1
+MSpppppapaa,muscle,1,ancestor,1.0,1,1
+MSpppppapap,muscle,1,ancestor,1.0,1,1
+MSpppppapapa,muscle,1,ancestor,1.0,1,1
+MSpppppapapaa,muscle,1,ancestor,1.0,1,1
+MSpppppapapap,muscle,1,ancestor,1.0,1,1
+MSpppppapapapa,muscle,1,ancestor,1.0,1,1
+MSpppppapapapp,muscle,1,ancestor,1.0,1,1
+MSpppppapapp,muscle,1,ancestor,1.0,1,1
+MSpppppapp,muscle,1,ancestor,1.0,1,1
+MSpppppp,muscle,1,exact,1.0,1,41
+MSppppppa,muscle,1,ancestor,1.0,1,1
+MSppppppp,muscle,1,ancestor,1.0,1,1
+Nuc1,unknown,12,unknown,0.0,0,1
+Nuc4,unknown,12,unknown,0.0,0,1
+P0,other,10,founder,1.0,0,8
+P1,mixed,11,founder,1.0,0,81
+P2,mixed,11,founder,1.0,0,255
+P3,mixed,11,founder,1.0,0,260
+P4,germline,6,founder,1.0,0,258
+Z2,germline,6,founder,1.0,0,222
+Z3,germline,6,founder,1.0,0,222
diff --git a/Spatio-Temporal-Evolution/Dataset/fate/name-function-each-cell.xlsx b/Spatio-Temporal-Evolution/Dataset/fate/name-function-each-cell.xlsx
new file mode 100644
index 0000000..cb25a7e
Binary files /dev/null and b/Spatio-Temporal-Evolution/Dataset/fate/name-function-each-cell.xlsx differ
diff --git a/Spatio-Temporal-Evolution/PROGRESS.md b/Spatio-Temporal-Evolution/PROGRESS.md
new file mode 100644
index 0000000..dd943e1
--- /dev/null
+++ b/Spatio-Temporal-Evolution/PROGRESS.md
@@ -0,0 +1,83 @@
+# Progress notes — Cell-fate reframe
+
+_Spatio-Temporal-Evolution (ESTGEL / DevoGraph GSoC) — 2026-07-23_
+
+## 1. Problem found
+The original **WT-vs-RNAi graph classification** was degenerate:
+- `labels.csv` was **254 "RNAi" vs 6 "control"**; val accuracy sat at exactly **0.9615 = 25/26**
+  (the majority base rate) — the model just predicted one class.
+- EPIC files are almost all **wild-type reporter strains**, not RNAi mutants, so the keyword
+  heuristic mislabeled ~254 WT embryos. EPIC has no real WT-vs-RNAi split.
+
+## 2. Dataset research
+Surveyed DevoWorm / SSBD / literature for data with a real signal (see `DATASET_MEMO.md`):
+- **RIKEN WDDD/SSBD RNAi** — 33 WT + 1142 RNAi, open BD5/BDML (~30 MB/embryo quantitative). Best
+  for a genuine perturbation split; shallow (~8-cell).
+- **CShaper atlas** — cell–cell contact maps to 350-cell (better edges; mostly WT).
+- **Digital Development DB** — ~1400 perturbed lineages with fate phenotypes (mutation dimension).
+
+## 3. Reframed target: cell-fate prediction
+The real goal is **predicting each cell's terminal fate from its division pattern + spatio-temporal
+context** — a **node-level** task, not whole-graph. Because the C. elegans lineage is invariant,
+fate labels come free from the cell name (Sulston), so **EPIC (already downloaded) is the right
+feature set**. Design rule: the **cell name is never a model feature** (that would be trivial
+leakage); fate is predicted from position / timing / contacts / expression only.
+
+## 4. Built this session (smoke-tested end-to-end on GPU)
+| File | What |
+|---|---|
+| `src/cell_fate.py` | 13-class fate taxonomy + `CellFateMap` (terminal desc → class; progenitor → consensus of descendant leaves w/ purity; `mixed` if uncommitted) + `fate_targets()` |
+| `scripts/build_cell_fate.py` | Generates the label map |
+| `Dataset/fate/cell_fate.csv` | **2,769 cells labeled**, 2 unknown; source `.xlsx` staged |
+| `src/estgel_node.py` | `ESTGELNodeClassifier` — reuses EAM→DRL→DNL, per-node embedding from `X_hat` → fate |
+| `scripts/train_fate.py` | By-embryo split, class-weighted loss, reports acc + **macro-F1 + per-class recall** |
+
+Label map source: DevoWorm `name-function-each-cell` (WormAtlas terminal descriptions),
+693/710 EPIC cells reconcile directly; occurrence-weighted distribution is healthy multi-class
+(neuron 18%, pharynx 16%, hypodermis 15%, muscle 12%, glia/intestine 5%, `mixed` 26%).
+
+## 5. Trained fate model (result)
+After fixing two real bugs — **no feature normalization** (blot ranged to 1.6e5 → exploding logits,
+loss 467; also explains why the original graph classifier never learned) and a **temporal-coverage
+bug** (fixed early window left ~70% of late-born cells with zero embeddings → all-"neuron" predictor)
+— the node classifier trains cleanly:
+
+- **Val accuracy 0.635, macro-F1 0.343** over 35 epochs (15 + 20 more with cosine LR decay;
+  was a fake plateau of 0.25 / 0.05 before the fixes). Plateaued — the remaining errors are the
+  genuinely hard cases, not a training-time issue.
+- Per-class recall: pharynx 0.80, hypodermis 0.72, muscle 0.72, neuron 0.62, intestine 0.60;
+  rare classes (glia/germline/excretory/coelomocyte) ~0 (dragged by <1% frequency; unweighted).
+- Checkpoint: `checkpoints/estgel_fate/best.pt` (feature-normalization stats saved in buffers).
+- Design rule kept: cell NAME is never a feature; fate predicted from position/size/expression + graph.
+
+## 6. Explainability (saliency / ablation, not attention)
+EAM attention is near-saturated (~0.9-1.0), so causal perturbation is used instead
+(`scripts/extract_fate_explainability.py`, `scripts/saliency_fate.py`):
+
+- **Interactions causally matter (validates ESTGEL):** removing ALL cell-cell edges drops accuracy
+  0.46 → 0.31 and **flips 40% of fate predictions**. Most edge-dependent: hypodermis, pharynx, neuron;
+  least: muscle, intestine.
+- **Feature importance by tissue:** position (x,y,z) dominates fate; **size** distinctively drives
+  intestine and pharynx; **blot (reporter expression) ≈ 0** — honest: the model uses geometry, not the
+  per-embryo reporter.
+- **Contact structure** (fate-annotated) is biologically sensible: like-fate cells cluster; intestine
+  is isolated from neuron; AB-derived pharynx/neuron/hypodermis intermix.
+- Artifacts: `fate_interaction_map.png`, `fate_saliency.png`, `fate_explainability.json`, `fate_saliency.json`.
+
+## 6b. Interactive dashboard / developmental simulation
+`dashboard/index.html` — self-contained (no CDNs, data inlined). Hand-rolled canvas 3D:
+rotatable embryo colored by predicted fate that **plays development forward** — smooth position
+interpolation across 30 frames, **cells divide** (daughters emerge from parents via lineage),
+**contact edges** drawn per frame, brightness by prediction confidence, red rings on misclassified
+cells (toggleable). Click-to-inspect (fate, confidence, true fate, parent, birth). Plus the
+causal-explainability panels (graph ablation, feature occlusion, contact map, training curve, per-class recall).
+Regenerate for any embryo: `python scripts/export_dashboard_data.py --embryo <name>.npz`
+(rebuilds the data + injects into `dashboard/fate_dashboard.template.html` -> `index.html`).
+The old WT/RNAi/attention dashboard (app.js/style.css/embryo_data.json/explainability_report.json)
+was retired.
+
+## 7. Next steps
+- Lift rare classes (√-capped class weighting already in `train_fate.py`, drop `--no-class-weight`).
+- Wire per-cell predicted fate + interactions into the 3D `dashboard/`.
+- Bring in Digital Development / WDDD for the **mutation → fate change** dimension.
+- Open decision (see `DATASET_MEMO.md`): confirm dataset direction with mentors.
diff --git a/Spatio-Temporal-Evolution/checkpoints/estgel_fate/config.json b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/config.json
new file mode 100644
index 0000000..acf03cc
--- /dev/null
+++ b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/config.json
@@ -0,0 +1,23 @@
+{
+  "processed_dir": "D:\\Github\\DevoGraph\\Spatio-Temporal-Evolution\\Dataset\\processed\\by_embryo",
+  "fate_csv": "D:\\Github\\DevoGraph\\Spatio-Temporal-Evolution\\Dataset\\fate\\cell_fate.csv",
+  "epochs": 20,
+  "lr": 0.001,
+  "weight_decay": 0.0001,
+  "val_ratio": 0.2,
+  "seed": 42,
+  "max_samples": null,
+  "recurrence_stride": 10,
+  "max_steps": 20,
+  "bptt_truncation": 3,
+  "K": 11,
+  "max_nodes": 1024,
+  "max_cells": 1000,
+  "drl_channels": 6,
+  "dropout": 0.5,
+  "no_class_weight": true,
+  "resume": true,
+  "cosine": true,
+  "checkpoint_dir": "D:\\Github\\DevoGraph\\Spatio-Temporal-Evolution\\checkpoints\\estgel_fate",
+  "device": "auto"
+}
\ No newline at end of file
diff --git a/Spatio-Temporal-Evolution/checkpoints/estgel_fate/fate_interaction_map.png b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/fate_interaction_map.png
new file mode 100644
index 0000000..d978895
Binary files /dev/null and b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/fate_interaction_map.png differ
diff --git a/Spatio-Temporal-Evolution/checkpoints/estgel_fate/fate_saliency.json b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/fate_saliency.json
new file mode 100644
index 0000000..4349ddf
--- /dev/null
+++ b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/fate_saliency.json
@@ -0,0 +1,116 @@
+{
+  "embryos_used": [
+    "CD20070219_Ges1-4.npz",
+    "CD20080303nob-1GFP.npz",
+    "CD20071212nob1GFP.npz",
+    "CD20060718_end3_2xx.npz",
+    "CD20080814_lin-13_6B12_1_L1.npz",
+    "CD20090331_fkh-4_11D3b24.npz"
+  ],
+  "features": [
+    "x",
+    "y",
+    "z",
+    "size",
+    "blot"
+  ],
+  "accuracy_full": 0.5045,
+  "accuracy_no_edges": 0.3129,
+  "prediction_flip_rate_no_edges": 0.4259,
+  "feature_occlusion_confdrop_by_fate": {
+    "pharynx": [
+      0.3636,
+      0.1373,
+      0.1912,
+      0.1712,
+      0.0009
+    ],
+    "neuron": [
+      0.2426,
+      0.2899,
+      0.1245,
+      -0.0124,
+      0.0017
+    ],
+    "muscle": [
+      0.122,
+      0.1462,
+      0.0385,
+      0.0668,
+      0.0044
+    ],
+    "intestine": [
+      -0.0116,
+      -0.019,
+      -0.0317,
+      0.1612,
+      -0.003
+    ],
+    "hypodermis": [
+      0.4126,
+      0.3506,
+      0.2226,
+      -0.0024,
+      -0.0043
+    ],
+    "glia": [
+      0.3464,
+      -0.0249,
+      0.2368,
+      0.1074,
+      0.0014
+    ]
+  },
+  "graph_ablation_confdrop_by_fate": {
+    "pharynx": 0.3205,
+    "neuron": 0.201,
+    "muscle": -0.0543,
+    "intestine": -0.0181,
+    "hypodermis": 0.4673,
+    "glia": 0.1086
+  },
+  "gradient_saliency_by_fate": {
+    "pharynx": [
+      0.0009,
+      0.0009,
+      0.0144,
+      0.0133,
+      0.0
+    ],
+    "neuron": [
+      0.0009,
+      0.0016,
+      0.0163,
+      0.0081,
+      0.0
+    ],
+    "muscle": [
+      0.0009,
+      0.0006,
+      0.0185,
+      0.0069,
+      0.0
+    ],
+    "intestine": [
+      0.0006,
+      0.0006,
+      0.0167,
+      0.0054,
+      0.0
+    ],
+    "hypodermis": [
+      0.0008,
+      0.001,
+      0.0174,
+      0.0096,
+      0.0
+    ],
+    "glia": [
+      0.0022,
+      0.0012,
+      0.0406,
+      0.0213,
+      0.0
+    ]
+  }
+}
\ No newline at end of file
diff --git a/Spatio-Temporal-Evolution/checkpoints/estgel_fate/fate_saliency.png b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/fate_saliency.png
new file mode 100644
index 0000000..411735d
Binary files /dev/null and b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/fate_saliency.png differ
diff --git a/Spatio-Temporal-Evolution/checkpoints/estgel_fate/history.json b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/history.json
new file mode 100644
index 0000000..4ea61d5
--- /dev/null
+++ b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/history.json
@@ -0,0 +1,282 @@
+[
+  {
+    "epoch": 1,
+    "train_loss": 1.7738347082322345,
+    "val_loss": 1.5323997969720877,
+    "val_acc": 0.40855956317772824,
+    "val_macro_f1": 0.1642926028665353,
+    "elapsed_s": 230.84316239999316
+  },
+  {
+    "epoch": 2,
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+    "val_loss": 1.4266734403722428,
+    "val_acc": 0.46366223179266325,
+    "val_macro_f1": 0.2126906765916178,
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+  },
+  {
+    "epoch": 3,
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+    "val_acc": 0.500461431977236,
+    "val_macro_f1": 0.24666610792967428,
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+  },
+  {
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+    "val_acc": 0.5116127047604399,
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+  {
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+    "val_macro_f1": 0.27673885603089127,
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+  {
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+  {
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+  {
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+  },
+  {
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+    "train_loss": 1.0147845042500518,
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+    "val_acc": 0.6353149273244636,
+    "val_macro_f1": 0.3425275739600494,
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+  },
+  {
+    "epoch": 33,
+    "train_loss": 1.01427889359746,
+    "val_loss": 1.0321694752749275,
+    "val_acc": 0.6350073060063063,
+    "val_macro_f1": 0.3424209048866277,
+    "elapsed_s": 240.0599455000047
+  },
+  {
+    "epoch": 34,
+    "train_loss": 1.0134412326674531,
+    "val_loss": 1.031846516272601,
+    "val_acc": 0.6348534953472276,
+    "val_macro_f1": 0.3425482474697184,
+    "elapsed_s": 220.76603690000775
+  },
+  {
+    "epoch": 35,
+    "train_loss": 1.0097422329124046,
+    "val_loss": 1.031866451104482,
+    "val_acc": 0.6348919480119972,
+    "val_macro_f1": 0.34262483796581894,
+    "elapsed_s": 216.84704000000784
+  }
+]
\ No newline at end of file
diff --git a/Spatio-Temporal-Evolution/checkpoints/estgel_fate/per_class_recall.json b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/per_class_recall.json
new file mode 100644
index 0000000..e817c0a
--- /dev/null
+++ b/Spatio-Temporal-Evolution/checkpoints/estgel_fate/per_class_recall.json
@@ -0,0 +1,12 @@
+{
+  "neuron": 0.615,
+  "muscle": 0.716,
+  "hypodermis": 0.721,
+  "pharynx": 0.8,
+  "intestine": 0.6,
+  "glia": 0.039,
+  "germline": 0.013,
+  "excretory": 0.0,
+  "coelomocyte": 0.0,
+  "other": 0.0
+}
\ No newline at end of file
diff --git a/Spatio-Temporal-Evolution/dashboard/app.js b/Spatio-Temporal-Evolution/dashboard/app.js
deleted file mode 100644
index 08fa110..0000000
--- a/Spatio-Temporal-Evolution/dashboard/app.js
+++ /dev/null
@@ -1,415 +0,0 @@
-// =========================================================================
-// ESTGEL 3D Visualisation Dashboard - Core Logic
-// =========================================================================
-
-let embryoData = null;
-let explainabilityReport = null;
-
-let currentPhenotype = "wt"; // "wt" or "rnai"
-let currentTimeStep = 30;
-
-// Three.js global variables
-let scene, camera, renderer, controls;
-let cellGroup, edgeGroup;
-
-// Chart.js global variables
-let growthChart = null;
-let attentionChart = null;
-let selectedInteraction = "ABalaaaal->ABalaaaar";
-
-// Helper function to color code cell lineages
-function getLineageColor(cellName) {
-    if (cellName.startsWith("AB")) {
-        return 0x00f2fe; // Cyan
-    } else if (cellName.startsWith("MS")) {
-        return 0xffd200; // Yellow
-    } else if (cellName.startsWith("E")) {
-        return 0x00e676; // Green
-    } else if (cellName.startsWith("C")) {
-        return 0xff9100; // Orange
-    } else if (cellName.startsWith("D")) {
-        return 0xf50057; // Pink
-    } else if (cellName.startsWith("P")) {
-        return 0xff1744; // Red
-    }
-    return 0xa0aec0; // Gray
-}
-
-// Helper to calculate average attention weight
-function getAverageAttention(attentions) {
-    const vals = Object.values(attentions);
-    if (vals.length === 0) return 0.0;
-    const sum = vals.reduce((a, b) => a + b, 0);
-    return sum / vals.length;
-}
-
-// Set up Three.js 3D Viewport
-function init3D() {
-    const container = document.getElementById("three-canvas-container");
-    const width = container.clientWidth;
-    const height = container.clientHeight;
-
-    scene = new THREE.Scene();
-    scene.background = new THREE.Color(0x080a0f);
-
-    camera = new THREE.PerspectiveCamera(45, width / height, 1, 1000);
-    // Align camera viewport dynamically
-    camera.position.set(100, 100, 300);
-
-    renderer = new THREE.WebGLRenderer({ antialias: true });
-    renderer.setSize(width, height);
-    container.appendChild(renderer.domElement);
-
-    controls = new THREE.OrbitControls(camera, renderer.domElement);
-    controls.enableDamping = true;
-    controls.dampingFactor = 0.05;
-    controls.maxPolarAngle = Math.PI;
-
-    // Add lighting
-    const ambientLight = new THREE.AmbientLight(0x222233);
-    scene.add(ambientLight);
-
-    const dirLight = new THREE.DirectionalLight(0xffffff, 1.2);
-    dirLight.position.set(200, 400, 300);
-    scene.add(dirLight);
-
-    const pointLight = new THREE.PointLight(0xffffff, 0.8, 500);
-    pointLight.position.set(0, 0, 0);
-    camera.add(pointLight);
-    scene.add(camera);
-
-    // Add Coordinate Grid Floor
-    const gridHelper = new THREE.GridHelper(400, 40, 0x4a5568, 0x1a202c);
-    gridHelper.position.y = -80;
-    scene.add(gridHelper);
-
-    cellGroup = new THREE.Group();
-    edgeGroup = new THREE.Group();
-    scene.add(cellGroup);
-    scene.add(edgeGroup);
-
-    // Handle window resize
-    window.addEventListener("resize", () => {
-        const w = container.clientWidth;
-        const h = container.clientHeight;
-        camera.aspect = w / h;
-        camera.updateProjectionMatrix();
-        renderer.setSize(w, h);
-    });
-
-    animate();
-}
-
-function animate() {
-    requestAnimationFrame(animate);
-    controls.update();
-    renderer.render(scene, camera);
-}
-
-// Render the 3D cell nodes and attention lines for a given timestep
-function update3DView() {
-    if (!embryoData || !explainabilityReport) return;
-
-    // 1. Clear previous meshes
-    while (cellGroup.children.length > 0) {
-        const obj = cellGroup.children[0];
-        obj.geometry.dispose();
-        obj.material.dispose();
-        cellGroup.remove(obj);
-    }
-    while (edgeGroup.children.length > 0) {
-        const obj = edgeGroup.children[0];
-        obj.geometry.dispose();
-        obj.material.dispose();
-        edgeGroup.remove(obj);
-    }
-
-    const typeKey = currentPhenotype; // "wt" or "rnai"
-    const tsKey = String(currentTimeStep);
-    const stepCells = embryoData[typeKey].timesteps[tsKey] || [];
-
-    // Map to quickly look up cell coordinates in 3D
-    const cellPosMap = {};
-
-    // Center of coordinates calculations for camera target focus
-    let cx = 0, cy = 0, cz = 0;
-
-    // 2. Draw Cell Nuclei Spheres
-    stepCells.forEach(cell => {
-        const [x, y, z] = cell.pos;
-        cx += x;
-        cy += y;
-        cz += z;
-
-        cellPosMap[cell.name] = new THREE.Vector3(x, y, z);
-
-        // Normalize and scale visual size
-        const radius = Math.max(3, cell.size * 0.4);
-        const geometry = new THREE.SphereGeometry(radius, 16, 16);
-        
-        // Color based on cell lineage (AB, MS, E, C, D)
-        const hexColor = getLineageColor(cell.name);
-        const material = new THREE.MeshPhongMaterial({
-            color: hexColor,
-            shininess: 80,
-            specular: 0x333333
-        });
-
-        const sphere = new THREE.Mesh(geometry, material);
-        sphere.position.set(x, y, z);
-        cellGroup.add(sphere);
-    });
-
-    // Reposition OrbitControls target to center of active cell mass
-    if (stepCells.length > 0) {
-        controls.target.set(cx / stepCells.length, cy / stepCells.length, cz / stepCells.length);
-    }
-
-    // 3. Draw Explainability Attention Edges
-    const reportKey = currentPhenotype + "_embryo";
-    const stepAttentions = explainabilityReport[reportKey].data.find(
-        d => d.timestep === currentTimeStep
-    );
-
-    let activeEdgesCount = 0;
-    let avgAttentionVal = 0.0;
-
-    if (stepAttentions && stepAttentions.attentions) {
-        const attentions = stepAttentions.attentions;
-        activeEdgesCount = Object.keys(attentions).length;
-        avgAttentionVal = getAverageAttention(attentions);
-
-        const edgeColor = currentPhenotype === "wt" ? 0x00f2fe : 0xff0844;
-
-        Object.entries(attentions).forEach(([connection, weight]) => {
-            const [srcName, dstName] = connection.split("->");
-            const srcPos = cellPosMap[srcName];
-            const dstPos = cellPosMap[dstName];
-
-            if (srcPos && dstPos) {
-                // Line weight maps to GNN attention weight
-                const material = new THREE.LineBasicMaterial({
-                    color: edgeColor,
-                    linewidth: weight * 3,
-                    transparent: true,
-                    opacity: Math.max(0.15, weight)
-                });
-
-                const points = [srcPos, dstPos];
-                const geometry = new THREE.BufferGeometry().setFromPoints(points);
-                const line = new THREE.Line(geometry, material);
-                edgeGroup.add(line);
-            }
-        });
-
-        // Update Top-5 sidebar interactions list
-        updateSidebarList(attentions);
-    } else {
-        updateSidebarList({});
-    }
-
-    // Update Stats Display panel
-    document.getElementById("stat-nodes").innerText = stepCells.length;
-    document.getElementById("stat-edges").innerText = activeEdgesCount;
-    document.getElementById("stat-avg-att").innerText = avgAttentionVal.toFixed(3);
-}
-
-// Render Top-5 GNN attention connections in the control panel
-function updateSidebarList(attentions) {
-    const list = document.getElementById("interaction-list");
-    list.innerHTML = "";
-
-    const sortedAtts = Object.entries(attentions)
-        .sort((a, b) => b[1] - a[1])
-        .slice(0, 5);
-
-    if (sortedAtts.length === 0) {
-        list.innerHTML = `<li class="interaction-item" style="color: #718096; justify-content: center;">No active connections at t=${currentTimeStep}</li>`;
-        return;
-    }
-
-    sortedAtts.forEach(([connection, weight]) => {
-        const li = document.createElement("li");
-        li.className = "interaction-item";
-        li.style.cursor = "pointer";
-        li.innerHTML = `
-            <span class="interaction-name">${connection}</span>
-            <span class="interaction-weight">${weight.toFixed(4)}</span>
-        `;
-        
-        // Clicking on an interaction details updates the Attention Trajectory Contrast Chart
-        li.addEventListener("click", () => {
-            selectedInteraction = connection;
-            updateAttentionChart();
-        });
-        
-        list.appendChild(li);
-    });
-}
-
-// Chart 1: Active Cell Growth curve using Chart.js
-function initGrowthChart() {
-    const ctx = document.getElementById("growthChart").getContext("2d");
-    
-    // Prepare time steps and counts
-    const steps = [30, 60, 90, 120, 150, 180];
-    const wtCounts = steps.map(t => (embryoData.wt.timesteps[String(t)] || []).length);
-    const rnaiCounts = steps.map(t => (embryoData.rnai.timesteps[String(t)] || []).length);
-
-    growthChart = new Chart(ctx, {
-        type: "line",
-        data: {
-            labels: steps.map(t => `t=${t}`),
-            datasets: [
-                {
-                    label: "Control (WT)",
-                    data: wtCounts,
-                    borderColor: "#4facfe",
-                    backgroundColor: "rgba(79, 172, 254, 0.1)",
-                    borderWidth: 2,
-                    tension: 0.2,
-                    fill: true
-                },
-                {
-                    label: "Perturbed (RNAi)",
-                    data: rnaiCounts,
-                    borderColor: "#ff0844",
-                    backgroundColor: "rgba(255, 8, 68, 0.1)",
-                    borderWidth: 2,
-                    borderDash: [4, 4],
-                    tension: 0.2,
-                    fill: true
-                }
-            ]
-        },
-        options: {
-            responsive: true,
-            maintainAspectRatio: false,
-            plugins: {
-                legend: { labels: { color: "#a0aec0", font: { family: "Outfit" } } }
-            },
-            scales: {
-                x: { grid: { color: "rgba(255,255,255,0.05)" }, ticks: { color: "#718096" } },
-                y: { grid: { color: "rgba(255,255,255,0.05)" }, ticks: { color: "#718096" } }
-            }
-        }
-    });
-}
-
-// Chart 2: EAM Attention Trajectory Contrast (WT vs. RNAi)
-function updateAttentionChart() {
-    const ctx = document.getElementById("attentionChart").getContext("2d");
-
-    const steps = [30, 60, 90, 120, 150, 180];
-    
-    // Extract trajectories for WT
-    const wtVals = steps.map(t => {
-        const step = explainabilityReport.wt_embryo.data.find(d => d.timestep === t);
-        return step ? (step.attentions[selectedInteraction] || 0.0) : 0.0;
-    });
-
-    // Extract trajectories for RNAi
-    const rnaiVals = steps.map(t => {
-        const step = explainabilityReport.rnai_embryo.data.find(d => d.timestep === t);
-        return step ? (step.attentions[selectedInteraction] || 0.0) : 0.0;
-    });
-
-    if (attentionChart) {
-        attentionChart.destroy();
-    }
-
-    attentionChart = new Chart(ctx, {
-        type: "line",
-        data: {
-            labels: steps.map(t => `t=${t}`),
-            datasets: [
-                {
-                    label: `WT: ${selectedInteraction}`,
-                    data: wtVals,
-                    borderColor: "#00f2fe",
-                    backgroundColor: "#00f2fe",
-                    borderWidth: 3,
-                    pointRadius: 4,
-                    tension: 0.1
-                },
-                {
-                    label: `RNAi: ${selectedInteraction}`,
-                    data: rnaiVals,
-                    borderColor: "#ff0844",
-                    backgroundColor: "#ff0844",
-                    borderWidth: 3,
-                    borderDash: [5, 5],
-                    pointRadius: 4,
-                    tension: 0.1
-                }
-            ]
-        },
-        options: {
-            responsive: true,
-            maintainAspectRatio: false,
-            plugins: {
-                legend: { labels: { color: "#a0aec0", font: { family: "Outfit" } } }
-            },
-            scales: {
-                x: { grid: { color: "rgba(255,255,255,0.05)" }, ticks: { color: "#718096" } },
-                y: { min: 0.0, max: 1.0, grid: { color: "rgba(255,255,255,0.05)" }, ticks: { color: "#718096" } }
-            }
-        }
-    });
-}
-
-// Fetch JSON data and initialize elements
-async function initDashboard() {
-    try {
-        console.log("Loading dashboard data...");
-        const [embryoRes, explainRes] = await Promise.all([
-            fetch("embryo_data.json"),
-            fetch("explainability_report.json")
-        ]);
-
-        embryoData = await embryoRes.json();
-        explainabilityReport = await explainRes.json();
-
-        console.log("Data loaded successfully.");
-
-        // Initialize visualization components
-        init3D();
-        initGrowthChart();
-        updateAttentionChart();
-        update3DView();
-
-        // Setup HTML UI Event Listeners
-        const btnWt = document.getElementById("btn-wt");
-        const btnRnai = document.getElementById("btn-rnai");
-        const slider = document.getElementById("time-slider");
-        const timeVal = document.getElementById("current-time-val");
-
-        btnWt.addEventListener("click", () => {
-            btnWt.classList.add("active");
-            btnRnai.classList.remove("active");
-            currentPhenotype = "wt";
-            update3DView();
-        });
-
-        btnRnai.addEventListener("click", () => {
-            btnRnai.classList.add("active");
-            btnWt.classList.remove("active");
-            currentPhenotype = "rnai";
-            update3DView();
-        });
-
-        slider.addEventListener("input", (e) => {
-            currentTimeStep = parseInt(e.target.value);
-            timeVal.innerText = currentTimeStep;
-            update3DView();
-        });
-
-    } catch (err) {
-        console.error("Error loading dashboard data:", err);
-        document.body.innerHTML = `<div style="display:flex; justify-content:center; align-items:center; height:100vh; color:red; font-size:18px;">
-            Error loading JSON data. Did you run the exporter script (python scripts/export_ui_data.py)?
-        </div>`;
-    }
-}
-
-window.addEventListener("DOMContentLoaded", initDashboard);
diff --git a/Spatio-Temporal-Evolution/dashboard/embryo_data.json b/Spatio-Temporal-Evolution/dashboard/embryo_data.json
deleted file mode 100644
index 7237f92..0000000
--- a/Spatio-Temporal-Evolution/dashboard/embryo_data.json
+++ /dev/null
@@ -1,12578 +0,0 @@
-{
-  "wt": {
-    "filename": "CD011505_end1red_bright.npz",
-    "total_timesteps": 220,
-    "timesteps": {
-      "30": [
-        {
-          "name": "ABala",
-          "pos": [
-            136.0,
-            276.0,
-            16.100000381469727
-          ],
-          "size": 62.0,
-          "blot": 86.0
-        },
-        {
-          "name": "ABalp",
-          "pos": [
-            169.0,
-            209.0,
-            12.699999809265137
-          ],
-          "size": 66.0,
-          "blot": -50.0
-        },
-        {
-          "name": "ABara",
-          "pos": [
-            284.0,
-            343.0,
-            11.300000190734863
-          ],
-          "size": 60.0,
-          "blot": 42.0
-        },
-        {
-          "name": "ABarp",
-          "pos": [
-            329.0,
-            369.0,
-            19.799999237060547
-          ],
-          "size": 66.0,
-          "blot": 218.0
-        },
-        {
-          "name": "ABpla",
-          "pos": [
-            284.0,
-            219.0,
-            22.0
-          ],
-          "size": 44.0,
-          "blot": -67.0
-        },
-        {
-          "name": "ABplp",
-          "pos": [
-            354.0,
-            170.0,
-            20.100000381469727
-          ],
-          "size": 46.0,
-          "blot": -49.0
-        },
-        {
-          "name": "ABpra",
-          "pos": [
-            436.0,
-            364.0,
-            10.300000190734863
-          ],
-          "size": 60.0,
-          "blot": 4.0
-        },
-        {
-          "name": "ABprp",
-          "pos": [
-            484.0,
-            291.0,
-            10.800000190734863
-          ],
-          "size": 66.0,
-          "blot": 32.0
-        },
-        {
-          "name": "C",
-          "pos": [
-            506.0,
-            300.0,
-            22.100000381469727
-          ],
-          "size": 72.0,
-          "blot": 44.0
-        },
-        {
-          "name": "E",
-          "pos": [
-            511.0,
-            163.0,
-            15.100000381469727
-          ],
-          "size": 72.0,
-          "blot": -93.0
-        },
-        {
-          "name": "MS",
-          "pos": [
-            348.0,
-            213.0,
-            10.100000381469727
-          ],
-          "size": 72.0,
-          "blot": 76.0
-        },
-        {
-          "name": "P3",
-          "pos": [
-            609.0,
-            217.0,
-            15.800000190734863
-          ],
-          "size": 66.0,
-          "blot": 9.0
-        }
-      ],
-      "60": [
-        {
-          "name": "ABalaa",
-          "pos": [
-            99.0,
-            261.0,
-            12.800000190734863
-          ],
-          "size": 64.0,
-          "blot": 48.0
-        },
-        {
-          "name": "ABalap",
-          "pos": [
-            156.0,
-            314.0,
-            19.799999237060547
-          ],
-          "size": 64.0,
-          "blot": 109.0
-        },
-        {
-          "name": "ABalpa",
-          "pos": [
-            148.0,
-            186.0,
-            12.899999618530273
-          ],
-          "size": 64.0,
-          "blot": -17.0
-        },
-        {
-          "name": "ABalpp",
-          "pos": [
-            250.0,
-            146.0,
-            20.799999237060547
-          ],
-          "size": 64.0,
-          "blot": 69.0
-        },
-        {
-          "name": "ABaraa",
-          "pos": [
-            186.0,
-            336.0,
-            10.5
-          ],
-          "size": 64.0,
-          "blot": -64.0
-        },
-        {
-          "name": "ABarap",
-          "pos": [
-            284.0,
-            378.0,
-            10.100000381469727
-          ],
-          "size": 66.0,
-          "blot": -63.0
-        },
-        {
-          "name": "ABarpa",
-          "pos": [
-            255.0,
-            381.0,
-            21.0
-          ],
-          "size": 66.0,
-          "blot": -7.0
-        },
-        {
-          "name": "ABarpp",
-          "pos": [
-            384.0,
-            374.0,
-            21.200000762939453
-          ],
-          "size": 68.0,
-          "blot": 49.0
-        },
-        {
-          "name": "ABplaa",
-          "pos": [
-            215.0,
-            254.0,
-            22.200000762939453
-          ],
-          "size": 68.0,
-          "blot": -172.0
-        },
-        {
-          "name": "ABplap",
-          "pos": [
-            328.0,
-            255.0,
-            23.0
-          ],
-          "size": 64.0,
-          "blot": 115.0
-        },
-        {
-          "name": "ABplpa",
-          "pos": [
-            336.0,
-            140.0,
-            20.700000762939453
-          ],
-          "size": 64.0,
-          "blot": 86.0
-        },
-        {
-          "name": "ABplpp",
-          "pos": [
-            451.0,
-            152.0,
-            21.899999618530273
-          ],
-          "size": 64.0,
-          "blot": 12.0
-        },
-        {
-          "name": "ABpraa",
-          "pos": [
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-            13.0
-          ],
-          "size": 64.0,
-          "blot": 69.0
-        },
-        {
-          "name": "ABprap",
-          "pos": [
-            483.0,
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-            17.0
-          ],
-          "size": 66.0,
-          "blot": 127.0
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-        {
-          "name": "ABprpa",
-          "pos": [
-            465.0,
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-            8.800000190734863
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-          "size": 64.0,
-          "blot": -19.0
-        },
-        {
-          "name": "ABprpp",
-          "pos": [
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-            11.699999809265137
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-          "size": 64.0,
-          "blot": -108.0
-        },
-        {
-          "name": "Ca",
-          "pos": [
-            436.0,
-            270.0,
-            21.899999618530273
-          ],
-          "size": 64.0,
-          "blot": 12.0
-        },
-        {
-          "name": "Cp",
-          "pos": [
-            561.0,
-            301.0,
-            19.200000762939453
-          ],
-          "size": 68.0,
-          "blot": 67.0
-        },
-        {
-          "name": "D",
-          "pos": [
-            612.0,
-            240.0,
-            15.699999809265137
-          ],
-          "size": 64.0,
-          "blot": -74.0
-        },
-        {
-          "name": "Ea",
-          "pos": [
-            414.0,
-            188.0,
-            11.300000190734863
-          ],
-          "size": 70.0,
-          "blot": 198.0
-        },
-        {
-          "name": "Ep",
-          "pos": [
-            513.0,
-            207.0,
-            13.0
-          ],
-          "size": 66.0,
-          "blot": 233.0
-        },
-        {
-          "name": "MSaa",
-          "pos": [
-            236.0,
-            214.0,
-            9.100000381469727
-          ],
-          "size": 48.0,
-          "blot": 20.0
-        },
-        {
-          "name": "MSap",
-          "pos": [
-            299.0,
-            181.0,
-            11.800000190734863
-          ],
-          "size": 64.0,
-          "blot": 69.0
-        },
-        {
-          "name": "MSpa",
-          "pos": [
-            329.0,
-            282.0,
-            9.300000190734863
-          ],
-          "size": 54.0,
-          "blot": -40.0
-        },
-        {
-          "name": "MSpp",
-          "pos": [
-            402.0,
-            285.0,
-            10.0
-          ],
-          "size": 54.0,
-          "blot": 14.0
-        },
-        {
-          "name": "P4",
-          "pos": [
-            566.0,
-            173.0,
-            9.399999618530273
-          ],
-          "size": 52.0,
-          "blot": -50.0
-        }
-      ],
-      "90": [
-        {
-          "name": "ABalaaa",
-          "pos": [
-            103.0,
-            299.0,
-            13.300000190734863
-          ],
-          "size": 54.0,
-          "blot": -109.0
-        },
-        {
-          "name": "ABalaap",
-          "pos": [
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-          ],
-          "size": 54.0,
-          "blot": -53.0
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-          "name": "ABalapa",
-          "pos": [
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-          "blot": -99.0
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-        {
-          "name": "ABalapp",
-          "pos": [
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-            15.800000190734863
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-          "size": 54.0,
-          "blot": -61.0
-        },
-        {
-          "name": "ABalpaa",
-          "pos": [
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-        },
-        {
-          "name": "ABalpap",
-          "pos": [
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-          "size": 54.0,
-          "blot": 17.0
-        },
-        {
-          "name": "ABalppa",
-          "pos": [
-            193.0,
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-            19.0
-          ],
-          "size": 54.0,
-          "blot": -32.0
-        },
-        {
-          "name": "ABalppp",
-          "pos": [
-            278.0,
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-          "blot": 131.0
-        },
-        {
-          "name": "ABaraaa",
-          "pos": [
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-            12.0
-          ],
-          "size": 54.0,
-          "blot": 14.0
-        },
-        {
-          "name": "ABaraap",
-          "pos": [
-            227.0,
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-            8.199999809265137
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-          "size": 54.0,
-          "blot": 33.0
-        },
-        {
-          "name": "ABarapa",
-          "pos": [
-            241.0,
-            386.0,
-            11.100000381469727
-          ],
-          "size": 54.0,
-          "blot": -161.0
-        },
-        {
-          "name": "ABarapp",
-          "pos": [
-            317.0,
-            377.0,
-            7.900000095367432
-          ],
-          "size": 54.0,
-          "blot": 43.0
-        },
-        {
-          "name": "ABarpaa",
-          "pos": [
-            211.0,
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-            20.0
-          ],
-          "size": 54.0,
-          "blot": 12.0
-        },
-        {
-          "name": "ABarpap",
-          "pos": [
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-        {
-          "name": "MSaapaap",
-          "pos": [
-            309.0,
-            318.0,
-            17.0
-          ],
-          "size": 34.0,
-          "blot": -112.0
-        },
-        {
-          "name": "MSaapap",
-          "pos": [
-            323.0,
-            309.0,
-            21.0
-          ],
-          "size": 36.0,
-          "blot": -275.0
-        },
-        {
-          "name": "MSaappa",
-          "pos": [
-            377.0,
-            304.0,
-            24.0
-          ],
-          "size": 36.0,
-          "blot": 515.0
-        },
-        {
-          "name": "MSaappp",
-          "pos": [
-            382.0,
-            345.0,
-            21.100000381469727
-          ],
-          "size": 36.0,
-          "blot": -1131.0
-        },
-        {
-          "name": "MSapaaa",
-          "pos": [
-            161.0,
-            323.0,
-            15.0
-          ],
-          "size": 36.0,
-          "blot": -134.0
-        },
-        {
-          "name": "MSapaap",
-          "pos": [
-            227.0,
-            332.0,
-            17.200000762939453
-          ],
-          "size": 36.0,
-          "blot": -326.0
-        },
-        {
-          "name": "MSapapa",
-          "pos": [
-            222.0,
-            345.0,
-            14.300000190734863
-          ],
-          "size": 36.0,
-          "blot": 483.0
-        },
-        {
-          "name": "MSapapp",
-          "pos": [
-            270.0,
-            341.0,
-            13.199999809265137
-          ],
-          "size": 36.0,
-          "blot": 465.0
-        },
-        {
-          "name": "MSappaa",
-          "pos": [
-            290.0,
-            355.0,
-            17.100000381469727
-          ],
-          "size": 36.0,
-          "blot": 938.0
-        },
-        {
-          "name": "MSappap",
-          "pos": [
-            341.0,
-            359.0,
-            19.100000381469727
-          ],
-          "size": 36.0,
-          "blot": 392.0
-        },
-        {
-          "name": "MSapppa",
-          "pos": [
-            322.0,
-            364.0,
-            14.199999809265137
-          ],
-          "size": 36.0,
-          "blot": -582.0
-        },
-        {
-          "name": "MSapppp",
-          "pos": [
-            370.0,
-            357.0,
-            12.300000190734863
-          ],
-          "size": 36.0,
-          "blot": 828.0
-        },
-        {
-          "name": "MSpaaaaa",
-          "pos": [
-            121.0,
-            231.0,
-            16.899999618530273
-          ],
-          "size": 32.0,
-          "blot": -756.0
-        },
-        {
-          "name": "MSpaaaap",
-          "pos": [
-            171.0,
-            222.0,
-            14.100000381469727
-          ],
-          "size": 36.0,
-          "blot": -271.0
-        },
-        {
-          "name": "MSpaaapa",
-          "pos": [
-            201.0,
-            206.0,
-            14.0
-          ],
-          "size": 32.0,
-          "blot": -124.0
-        },
-        {
-          "name": "MSpaaapp",
-          "pos": [
-            250.0,
-            219.0,
-            11.300000190734863
-          ],
-          "size": 34.0,
-          "blot": -360.0
-        },
-        {
-          "name": "MSpaapa",
-          "pos": [
-            233.0,
-            218.0,
-            16.200000762939453
-          ],
-          "size": 36.0,
-          "blot": 85.0
-        },
-        {
-          "name": "MSpaapp",
-          "pos": [
-            290.0,
-            187.0,
-            19.0
-          ],
-          "size": 32.0,
-          "blot": 1148.0
-        },
-        {
-          "name": "MSpapaaa",
-          "pos": [
-            269.0,
-            282.0,
-            21.100000381469727
-          ],
-          "size": 36.0,
-          "blot": 212.0
-        },
-        {
-          "name": "MSpapaap",
-          "pos": [
-            308.0,
-            259.0,
-            19.100000381469727
-          ],
-          "size": 36.0,
-          "blot": -289.0
-        },
-        {
-          "name": "MSpapap",
-          "pos": [
-            349.0,
-            258.0,
-            20.299999237060547
-          ],
-          "size": 36.0,
-          "blot": -126.0
-        },
-        {
-          "name": "MSpappa",
-          "pos": [
-            365.0,
-            255.0,
-            24.100000381469727
-          ],
-          "size": 36.0,
-          "blot": 861.0
-        },
-        {
-          "name": "MSpappp",
-          "pos": [
-            421.0,
-            268.0,
-            23.100000381469727
-          ],
-          "size": 36.0,
-          "blot": 345.0
-        },
-        {
-          "name": "MSppaaa",
-          "pos": [
-            185.0,
-            197.0,
-            19.0
-          ],
-          "size": 36.0,
-          "blot": -666.0
-        },
-        {
-          "name": "MSppaap",
-          "pos": [
-            230.0,
-            184.0,
-            22.0
-          ],
-          "size": 36.0,
-          "blot": 641.0
-        },
-        {
-          "name": "MSppapa",
-          "pos": [
-            248.0,
-            169.0,
-            18.100000381469727
-          ],
-          "size": 36.0,
-          "blot": -1184.0
-        },
-        {
-          "name": "MSppapp",
-          "pos": [
-            300.0,
-            158.0,
-            15.100000381469727
-          ],
-          "size": 36.0,
-          "blot": -580.0
-        },
-        {
-          "name": "MSpppaa",
-          "pos": [
-            289.0,
-            200.0,
-            22.0
-          ],
-          "size": 29.0,
-          "blot": -8.0
-        },
-        {
-          "name": "MSpppap",
-          "pos": [
-            352.0,
-            188.0,
-            21.100000381469727
-          ],
-          "size": 36.0,
-          "blot": -642.0
-        },
-        {
-          "name": "MSppppa",
-          "pos": [
-            339.0,
-            156.0,
-            17.100000381469727
-          ],
-          "size": 36.0,
-          "blot": -117.0
-        },
-        {
-          "name": "MSppppp",
-          "pos": [
-            389.0,
-            157.0,
-            14.100000381469727
-          ],
-          "size": 36.0,
-          "blot": 1300.0
-        }
-      ]
-    }
-  }
-}
\ No newline at end of file
diff --git a/Spatio-Temporal-Evolution/dashboard/explainability_report.json b/Spatio-Temporal-Evolution/dashboard/explainability_report.json
deleted file mode 100644
index 9dacef8..0000000
--- a/Spatio-Temporal-Evolution/dashboard/explainability_report.json
+++ /dev/null
@@ -1,2365 +0,0 @@
-{
-  "wt_embryo": {
-    "filename": "CD011505_end1red_bright.npz",
-    "timesteps": [
-      30,
-      60,
-      90,
-      120,
-      150,
-      180
-    ],
-    "data": [
-      {
-        "timestep": 30,
-        "attentions": {
-          "ABal->ABala": 1.0,
-          "ABal->ABalp": 1.0,
-          "ABar->ABara": 0.9123597741127014,
-          "ABar->ABarp": 0.9123597741127014,
-          "ABpl->ABpla": 0.9123597741127014,
-          "ABpl->ABplp": 0.9123597741127014,
-          "ABpr->ABpra": 0.9123597741127014,
-          "ABpr->ABprp": 0.9123597741127014
-        }
-      },
-      {
-        "timestep": 60,
-        "attentions": {
-          "ABala->ABalaa": 0.9123597741127014,
-          "ABala->ABalap": 0.9123597741127014,
-          "ABalp->ABalpa": 0.9123597741127014,
-          "ABalp->ABalpp": 0.9123597741127014,
-          "ABara->ABaraa": 0.9123597741127014,
-          "ABara->ABarap": 0.9123597741127014,
-          "ABarp->ABarpa": 0.9123597741127014,
-          "ABarp->ABarpp": 0.9123597741127014,
-          "ABpla->ABplaa": 0.9123597741127014,
-          "ABpla->ABplap": 0.9123597741127014,
-          "ABplp->ABplpa": 0.9123597741127014,
-          "ABplp->ABplpp": 0.9123597741127014,
-          "ABpra->ABpraa": 0.9123597741127014,
-          "ABpra->ABprap": 0.9123597741127014,
-          "ABprp->ABprpa": 0.9123597741127014,
-          "ABprp->ABprpp": 0.9123597741127014,
-          "MSa->MSaa": 0.9123597741127014,
-          "MSa->MSap": 0.9123597741127014,
-          "MSp->MSpa": 0.9123597741127014,
-          "MSp->MSpp": 0.9123597741127014,
-          "E->Ea": 0.9123597741127014,
-          "E->Ep": 0.9123597741127014,
-          "C->Ca": 0.9123597741127014,
-          "C->Cp": 0.9123597741127014
-        }
-      },
-      {
-        "timestep": 90,
-        "attentions": {
-          "ABalpap->ABalppa": 1.0,
-          "ABalppa->ABalpap": 1.0,
-          "ABarpap->MSpaa": 1.0,
-          "MSpaa->ABarpap": 1.0,
-          "Epr->Cpa": 1.0,
-          "Cpa->Epr": 1.0,
-          "Cpp->Dp": 0.9123597741127014,
-          "Dp->Cpp": 0.9123597741127014,
-          "ABalaa->ABalaaa": 0.9123597741127014,
-          "ABalaa->ABalaap": 0.8292930126190186,
-          "ABalap->ABalapa": 0.9123597741127014,
-          "ABalap->ABalapp": 0.9123597741127014,
-          "ABalpa->ABalpaa": 0.9123597741127014,
-          "ABalpa->ABalpap": 0.9123597741127014,
-          "ABalpp->ABalppa": 0.9123597741127014,
-          "ABalpp->ABalppp": 0.9123597741127014,
-          "ABaraa->ABaraaa": 0.9123597741127014,
-          "ABaraa->ABaraap": 0.9123597741127014,
-          "ABarap->ABarapa": 0.9123597741127014,
-          "ABarap->ABarapp": 0.9123597741127014,
-          "ABarpa->ABarpaa": 0.9123597741127014,
-          "ABarpa->ABarpap": 0.9123597741127014,
-          "ABarpp->ABarppa": 0.9123597741127014,
-          "ABarpp->ABarppp": 0.9123597741127014,
-          "ABplaa->ABplaaa": 0.9123597741127014,
-          "ABplaa->ABplaap": 0.9123597741127014,
-          "ABplap->ABplapa": 0.9123597741127014,
-          "ABplap->ABplapp": 0.9123597741127014,
-          "ABplpa->ABplpaa": 0.9123597741127014,
-          "ABplpa->ABplpap": 0.9123597741127014,
-          "ABplpp->ABplppa": 0.9123597741127014,
-          "ABplpp->ABplppp": 0.9123597741127014,
-          "ABpraa->ABpraaa": 0.9123597741127014,
-          "ABpraa->ABpraap": 0.9123597741127014,
-          "ABprap->ABprapa": 0.9123597741127014,
-          "ABprap->ABprapp": 0.9123597741127014,
-          "ABprpa->ABprpaa": 0.9123597741127014,
-          "ABprpa->ABprpap": 0.9123597741127014,
-          "ABprpp->ABprppa": 0.9123597741127014,
-          "ABprpp->ABprppp": 0.9123597741127014,
-          "MSaa->MSaaa": 0.9123597741127014,
-          "MSaa->MSaap": 0.9123597741127014,
-          "MSap->MSapa": 0.8292930126190186,
-          "MSap->MSapp": 0.9123597741127014,
-          "MSpa->MSpaa": 0.9123597741127014,
-          "MSpa->MSpap": 0.8292930126190186,
-          "MSpp->MSppa": 0.9123597741127014,
-          "MSpp->MSppp": 0.9123597741127014,
-          "Ea->Eal": 0.9123597741127014,
-          "Ea->Ear": 0.8292930126190186,
-          "Ep->Epl": 0.9123597741127014,
-          "Ep->Epr": 0.9123597741127014,
-          "Ca->Caa": 0.8292930126190186,
-          "Ca->Cap": 0.9123597741127014,
-          "Cp->Cpa": 0.9123597741127014,
-          "Cp->Cpp": 0.9123597741127014,
-          "D->Da": 0.9123597741127014,
-          "D->Dp": 0.9123597741127014
-        }
-      },
-      {
-        "timestep": 120,
-        "attentions": {
-          "ABalaapp->ABplapaa": 0.9123597741127014,
-          "ABplapaa->ABalaapp": 0.9123597741127014,
-          "ABalapap->ABaraapa": 0.9123597741127014,
-          "ABaraapa->ABalapap": 0.9123597741127014,
-          "ABalappp->ABaraapp": 0.9123597741127014,
-          "ABaraapp->ABalappp": 0.9123597741127014,
-          "ABalappp->ABplapaa": 1.0,
-          "ABplapaa->ABalappp": 1.0,
-          "ABarappp->ABarpppa": 1.0,
-          "ABarpppa->ABarappp": 1.0,
-          "ABplappa->MSaapp": 0.9123597741127014,
-          "MSaapp->ABplappa": 0.9123597741127014,
-          "ABplappp->MSapp": 0.9123597741127014,
-          "MSapp->ABplappp": 0.9123597741127014,
-          "ABpraapp->ABprapaa": 0.9123597741127014,
-          "ABprapaa->ABpraapp": 0.9123597741127014,
-          "ABprappp->ABprpppa": 0.9123597741127014,
-          "ABprpppa->ABprappp": 0.9123597741127014,
-          "MSppp->Epr": 0.9123597741127014,
-          "Epr->MSppp": 0.9123597741127014,
-          "ABalaaa->ABalaaaa": 0.9123597741127014,
-          "ABalaaa->ABalaaap": 0.9123597741127014,
-          "ABalaap->ABalaapa": 0.8292930126190186,
-          "ABalaap->ABalaapp": 0.9123597741127014,
-          "ABalapa->ABalapaa": 0.8292930126190186,
-          "ABalapa->ABalapap": 0.9123597741127014,
-          "ABalapp->ABalappa": 0.8292930126190186,
-          "ABalapp->ABalappp": 0.9123597741127014,
-          "ABalpaa->ABalpaaa": 0.8292930126190186,
-          "ABalpaa->ABalpaap": 0.8292930126190186,
-          "ABalpap->ABalpapa": 0.9123597741127014,
-          "ABalpap->ABalpapp": 0.9123597741127014,
-          "ABalppa->ABalppaa": 0.9123597741127014,
-          "ABalppa->ABalppap": 0.9123597741127014,
-          "ABalppp->ABalpppa": 0.9123597741127014,
-          "ABalppp->ABalpppp": 0.9123597741127014,
-          "ABaraaa->ABaraaaa": 0.8292930126190186,
-          "ABaraaa->ABaraaap": 0.8292930126190186,
-          "ABaraap->ABaraapa": 0.9123597741127014,
-          "ABaraap->ABaraapp": 0.9123597741127014,
-          "ABarapa->ABarapaa": 0.8292930126190186,
-          "ABarapa->ABarapap": 0.8292930126190186,
-          "ABarapp->ABarappa": 0.8292930126190186,
-          "ABarapp->ABarappp": 0.9123597741127014,
-          "ABarpaa->ABarpaaa": 0.8292930126190186,
-          "ABarpaa->ABarpaap": 0.8292930126190186,
-          "ABarpap->ABarpapa": 0.8292930126190186,
-          "ABarpap->ABarpapp": 0.8292930126190186,
-          "ABarppa->ABarppaa": 0.8292930126190186,
-          "ABarppa->ABarppap": 0.8292930126190186,
-          "ABarppp->ABarpppa": 0.9123597741127014,
-          "ABarppp->ABarpppp": 0.8292930126190186,
-          "ABplaaa->ABplaaaa": 0.8292930126190186,
-          "ABplaaa->ABplaaap": 0.8292930126190186,
-          "ABplaap->ABplaapa": 0.8292930126190186,
-          "ABplaap->ABplaapp": 0.8292930126190186,
-          "ABplapa->ABplapaa": 0.9123597741127014,
-          "ABplapa->ABplapap": 0.8292930126190186,
-          "ABplapp->ABplappa": 0.9123597741127014,
-          "ABplapp->ABplappp": 0.9123597741127014,
-          "ABplpaa->ABplpaaa": 0.8292930126190186,
-          "ABplpaa->ABplpaap": 0.8292930126190186,
-          "ABplpap->ABplpapa": 0.8292930126190186,
-          "ABplpap->ABplpapp": 0.8292930126190186,
-          "ABplppa->ABplppaa": 0.8292930126190186,
-          "ABplppa->ABplppap": 0.8292930126190186,
-          "ABplppp->ABplpppa": 0.8292930126190186,
-          "ABplppp->ABplpppp": 0.8292930126190186,
-          "ABpraaa->ABpraaaa": 0.8292930126190186,
-          "ABpraaa->ABpraaap": 0.8292930126190186,
-          "ABpraap->ABpraapa": 0.8292930126190186,
-          "ABpraap->ABpraapp": 0.9123597741127014,
-          "ABprapa->ABprapaa": 0.9123597741127014,
-          "ABprapa->ABprapap": 0.8292930126190186,
-          "ABprapp->ABprappa": 0.8292930126190186,
-          "ABprapp->ABprappp": 0.9123597741127014,
-          "ABprpaa->ABprpaaa": 0.8292930126190186,
-          "ABprpaa->ABprpaap": 0.8292930126190186,
-          "ABprpap->ABprpapa": 0.8292930126190186,
-          "ABprpap->ABprpapp": 0.8292930126190186,
-          "ABprppa->ABprppaa": 0.8292930126190186,
-          "ABprppa->ABprppap": 0.8292930126190186,
-          "ABprppp->ABprpppa": 0.9123597741127014,
-          "ABprppp->ABprpppp": 0.8292930126190186,
-          "MSaaa->MSaaaa": 0.8292930126190186,
-          "MSaaa->MSaaap": 0.8292930126190186,
-          "MSaap->MSaapa": 0.8292930126190186,
-          "MSaap->MSaapp": 0.9123597741127014,
-          "MSap->MSapa": 0.8292930126190186,
-          "MSap->MSapp": 0.9123597741127014,
-          "MSpa->MSpaa": 0.8292930126190186,
-          "MSpa->MSpap": 0.8292930126190186,
-          "MSpp->MSppa": 0.8292930126190186,
-          "MSpp->MSppp": 0.9123597741127014,
-          "Ea->Eal": 0.8292930126190186,
-          "Ea->Ear": 0.8292930126190186,
-          "Ep->Epl": 0.8292930126190186,
-          "Ep->Epr": 0.9123597741127014,
-          "Caa->Caaa": 0.8292930126190186,
-          "Caa->Caap": 0.8292930126190186,
-          "Cap->Capa": 0.8292930126190186,
-          "Cap->Capp": 0.8292930126190186,
-          "Cpa->Cpaa": 0.8292930126190186,
-          "Cpa->Cpap": 0.8292930126190186,
-          "Cpp->Cppa": 0.8292930126190186,
-          "Cpp->Cppp": 0.8292930126190186,
-          "D->Da": 0.8292930126190186,
-          "D->Dp": 0.8292930126190186
-        }
-      },
-      {
-        "timestep": 150,
-        "attentions": {
-          "ABalaaaal->ABalaaaar": 1.0,
-          "ABalaaaar->ABalaaaal": 1.0,
-          "ABalaaaal->ABalpaaaa": 0.9123597741127014,
-          "ABalpaaaa->ABalaaaal": 0.9123597741127014,
-          "ABalaaaar->ABaraaaaa": 0.9123597741127014,
-          "ABaraaaaa->ABalaaaar": 0.9123597741127014,
-          "ABalaaapa->ABalaapaa": 0.8292930126190186,
-          "ABalaapaa->ABalaaapa": 0.8292930126190186,
-          "ABalaaapp->ABalappap": 0.9123597741127014,
-          "ABalappap->ABalaaapp": 0.9123597741127014,
-          "ABalaaapp->ABarapaaa": 0.9123597741127014,
-          "ABarapaaa->ABalaaapp": 0.9123597741127014,
-          "ABalaapap->ABalaappa": 0.8292930126190186,
-          "ABalaappa->ABalaapap": 0.8292930126190186,
-          "ABalaappp->ABaraaapp": 0.9123597741127014,
-          "ABaraaapp->ABalaappp": 0.9123597741127014,
-          "ABalapaaa->MSaaaa": 0.9123597741127014,
-          "MSaaaa->ABalapaaa": 0.9123597741127014,
-          "ABalapaap->ABalpppaa": 0.8292930126190186,
-          "ABalpppaa->ABalapaap": 0.8292930126190186,
-          "ABalapapp->MSaaap": 0.8292930126190186,
-          "MSaaap->ABalapapp": 0.8292930126190186,
-          "ABalappap->ABarapaaa": 0.9123597741127014,
-          "ABarapaaa->ABalappap": 0.9123597741127014,
-          "ABalapppa->ABarpaaap": 0.9123597741127014,
-          "ABarpaaap->ABalapppa": 0.9123597741127014,
-          "ABalpaaap->ABalpaapp": 1.0,
-          "ABalpaapp->ABalpaaap": 1.0,
-          "ABalpaaap->ABplaaaaa": 0.9123597741127014,
-          "ABplaaaaa->ABalpaaap": 0.9123597741127014,
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-          "ABplppapp->ABplpppaa": 0.9123597741127014,
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-          "Caaaa->Daa": 0.8292930126190186,
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-          "Dpp->Cpaap": 0.8292930126190186,
-          "ABalaaaa->ABalaaaal": 0.8292930126190186,
-          "ABalaaaa->ABalaaaar": 0.8292930126190186,
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-          "ABalaapa->ABalaapaa": 0.761333703994751,
-          "ABalaapa->ABalaapap": 0.761333703994751,
-          "ABalaapp->ABalaappa": 0.761333703994751,
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-          "ABalppap->ABalppapp": 0.761333703994751,
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-          "ABalpppa->ABalpppap": 0.761333703994751,
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-          "ABarappa->ABarappaa": 0.761333703994751,
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-          "ABarpaaa->ABarpaaaa": 0.8292930126190186,
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-          "ABarpaap->ABarpaapa": 0.761333703994751,
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-          "ABarpapp->ABarpappp": 0.761333703994751,
-          "ABarppaa->ABarppaaa": 0.761333703994751,
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-          "ABarpppa->ABarpppap": 0.8292930126190186,
-          "ABarppp->ABarpppp": 0.761333703994751,
-          "ABplaaaa->ABplaaaaa": 0.8292930126190186,
-          "ABplaaaa->ABplaaaap": 0.8292930126190186,
-          "ABplaaap->ABplaaapa": 0.6432212591171265,
-          "ABplaaap->ABplaaapp": 0.761333703994751,
-          "ABplaapa->ABplaapaa": 0.6432212591171265,
-          "ABplaapa->ABplaapap": 0.6432212591171265,
-          "ABplaapp->ABplaappa": 0.8292930126190186,
-          "ABplaapp->ABplaappp": 0.6432212591171265,
-          "ABplapaa->ABplapaaa": 0.8292930126190186,
-          "ABplapaa->ABplapaap": 0.6432212591171265,
-          "ABplapap->ABplapapa": 0.6432212591171265,
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-          "ABplappa->ABplappaa": 0.8292930126190186,
-          "ABplappa->ABplappap": 0.8292930126190186,
-          "ABplappp->ABplapppa": 0.6432212591171265,
-          "ABplappp->ABplapppp": 0.6432212591171265,
-          "ABplpaaa->ABplpaaaa": 0.6432212591171265,
-          "ABplpaaa->ABplpaaap": 0.8292930126190186,
-          "ABplpaap->ABplpaapa": 0.6432212591171265,
-          "ABplpaap->ABplpaapp": 0.8292930126190186,
-          "ABplpapa->ABplpapaa": 0.6432212591171265,
-          "ABplpapa->ABplpapap": 0.6432212591171265,
-          "ABplpapp->ABplpappa": 0.761333703994751,
-          "ABplpapp->ABplpappp": 0.6432212591171265,
-          "ABplppaa->ABplppaaa": 0.6432212591171265,
-          "ABplppaa->ABplppaap": 0.6432212591171265,
-          "ABplppap->ABplppapa": 0.761333703994751,
-          "ABplppap->ABplppapp": 0.761333703994751,
-          "ABplpppa->ABplpppaa": 0.761333703994751,
-          "ABplpppa->ABplpppap": 0.761333703994751,
-          "ABplpppp->ABplppppa": 0.761333703994751,
-          "ABplpppp->ABplppppp": 0.6432212591171265,
-          "ABpraaaa->ABpraaaaa": 0.761333703994751,
-          "ABpraaaa->ABpraaaap": 0.6432212591171265,
-          "ABpraaap->ABpraaapa": 0.6432212591171265,
-          "ABpraaap->ABpraaapp": 0.761333703994751,
-          "ABpraapa->ABpraapaa": 0.8292930126190186,
-          "ABpraapa->ABpraapap": 0.8292930126190186,
-          "ABpraapp->ABpraappa": 0.761333703994751,
-          "ABpraapp->ABpraappp": 0.761333703994751,
-          "ABprapaa->ABprapaaa": 0.8292930126190186,
-          "ABprapaa->ABprapaap": 0.8292930126190186,
-          "ABprapap->ABprapapa": 0.8292930126190186,
-          "ABprapap->ABprapapp": 0.8292930126190186,
-          "ABprappa->ABprappaa": 0.8292930126190186,
-          "ABprappa->ABprappap": 0.8292930126190186,
-          "ABprappp->ABprapppa": 0.6432212591171265,
-          "ABprappp->ABprapppp": 0.8292930126190186,
-          "ABprpaaa->ABprpaaaa": 0.6432212591171265,
-          "ABprpaaa->ABprpaaap": 0.6432212591171265,
-          "ABprpaap->ABprpaapa": 0.6432212591171265,
-          "ABprpaap->ABprpaapp": 0.6432212591171265,
-          "ABprpapa->ABprpapaa": 0.6432212591171265,
-          "ABprpapa->ABprpapap": 0.6432212591171265,
-          "ABprpapp->ABprpappa": 0.6432212591171265,
-          "ABprpapp->ABprpappp": 0.761333703994751,
-          "ABprppaa->ABprppaaa": 0.761333703994751,
-          "ABprppaa->ABprppaap": 0.761333703994751,
-          "ABprppap->ABprppapa": 0.761333703994751,
-          "ABprppap->ABprppapp": 0.761333703994751,
-          "ABprpppa->ABprpppaa": 0.8292930126190186,
-          "ABprpppa->ABprpppap": 0.6432212591171265,
-          "ABprpppp->ABprppppa": 0.761333703994751,
-          "ABprpppp->ABprppppp": 0.6432212591171265,
-          "MSaaa->MSaaaa": 0.761333703994751,
-          "MSaaa->MSaaap": 0.761333703994751,
-          "MSaap->MSaapa": 0.761333703994751,
-          "MSaap->MSaapp": 0.761333703994751,
-          "MSapa->MSapaa": 0.761333703994751,
-          "MSapa->MSapap": 0.761333703994751,
-          "MSapp->MSappa": 0.6432212591171265,
-          "MSapp->MSappp": 0.6432212591171265,
-          "MSpaa->MSpaaa": 0.6432212591171265,
-          "MSpaa->MSpaap": 0.761333703994751,
-          "MSpap->MSpapa": 0.6432212591171265,
-          "MSpap->MSpapp": 0.6432212591171265,
-          "MSppa->MSppaa": 0.761333703994751,
-          "MSppa->MSppap": 0.761333703994751,
-          "MSppp->MSpppa": 0.8292930126190186,
-          "MSppp->MSpppp": 0.761333703994751,
-          "Eal->Eala": 0.8292930126190186,
-          "Eal->Ealp": 0.8292930126190186,
-          "Ear->Eara": 0.761333703994751,
-          "Ear->Earp": 0.6432212591171265,
-          "Epl->Epla": 0.6432212591171265,
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-          "Caaa->Caaaa": 0.761333703994751,
-          "Caaa->Caaap": 0.6432212591171265,
-          "Caa->Caap": 0.6432212591171265,
-          "Cap->Capa": 0.6432212591171265,
-          "Cap->Capp": 0.6432212591171265,
-          "Cpaa->Cpaaa": 0.8292930126190186,
-          "Cpaa->Cpaap": 0.8292930126190186,
-          "Cpap->Cpapa": 0.6432212591171265,
-          "Cpap->Cpapp": 0.6432212591171265,
-          "Cpp->Cppa": 0.6432212591171265,
-          "Cppp->Cpppa": 0.6432212591171265,
-          "Cppp->Cpppp": 0.6432212591171265,
-          "Da->Daa": 0.761333703994751,
-          "Da->Dap": 0.6432212591171265,
-          "Dp->Dpa": 0.6432212591171265,
-          "Dp->Dpp": 0.761333703994751
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-        "timestep": 180,
-        "attentions": {
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-          "ABalaaapp->ABaraaaaa": 0.8292930126190186,
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-          "ABalappap->ABaraaapa": 0.8292930126190186,
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-          "ABalapppp->MSppaap": 1.0,
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-          "MSaaaaa->ABalpaaaa": 0.8292930126190186,
-          "ABalpaaap->MSaaaap": 0.8292930126190186,
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-          "MSapaap->ABalpapap": 0.8292930126190186,
-          "ABalpapppa->ABarapapa": 0.8292930126190186,
-          "ABarapapa->ABalpapppa": 0.8292930126190186,
-          "ABalppaaa->ABalpppaa": 0.9123597741127014,
-          "ABalpppaa->ABalppaaa": 0.9123597741127014,
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-          "ABalppapa->ABplaapaa": 0.9123597741127014,
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-          "MSpaapa->ABaraappp": 0.8292930126190186,
-          "ABarapaap->MSpaaap": 0.8292930126190186,
-          "MSpaaap->ABarapaap": 0.8292930126190186,
-          "ABarapapa->ABarpaapa": 0.9123597741127014,
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-          "ABarappaa->MSppaap": 0.9123597741127014,
-          "MSppaap->ABarappaa": 0.9123597741127014,
-          "ABarappap->MSppapa": 0.9123597741127014,
-          "MSppapa->ABarappap": 0.9123597741127014,
-          "ABarapppp->ABpraaapp": 0.9123597741127014,
-          "ABpraaapp->ABarapppp": 0.9123597741127014,
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-          "MSpppap->ABprpappa": 0.8292930126190186,
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-          "Epra->ABprpappp": 0.8292930126190186,
-          "ABprppapp->ABprpppaa": 0.8292930126190186,
-          "ABprpppaa->ABprppapp": 0.8292930126190186,
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-          "Caapp->Caapa": 0.761333703994751,
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-          "ABalaaaa->ABalaaaar": 0.6432212591171265,
-          "ABalaaap->ABalaaapa": 0.6432212591171265,
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-          "ABalaapa->ABalaapaa": 0.5572793483734131,
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-          "ABalaapp->ABalaappp": 0.6432212591171265,
-          "ABalapaa->ABalapaaa": 0.6432212591171265,
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-          "ABalappp->ABalapppa": 0.6432212591171265,
-          "ABalappp->ABalapppp": 0.761333703994751,
-          "ABalpaaa->ABalpaaaa": 0.6432212591171265,
-          "ABalpaaa->ABalpaaap": 0.6432212591171265,
-          "ABalpaapa->ABalpaapaa": 0.6432212591171265,
-          "ABalpaapa->ABalpaapap": 0.6432212591171265,
-          "ABalpaap->ABalpaapp": 0.6432212591171265,
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-          "ABalpapp->ABalpappa": 0.6432212591171265,
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-          "ABalppaa->ABalppaaa": 0.6432212591171265,
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-          "ABalppap->ABalppapa": 0.6432212591171265,
-          "ABalppap->ABalppapp": 0.6432212591171265,
-          "ABalpppa->ABalpppaa": 0.761333703994751,
-          "ABalpppa->ABalpppap": 0.761333703994751,
-          "ABalpppp->ABalppppa": 0.761333703994751,
-          "ABalpppp->ABalppppp": 0.761333703994751,
-          "ABaraaaa->ABaraaaaa": 0.761333703994751,
-          "ABaraaaa->ABaraaaap": 0.6432212591171265,
-          "ABaraaap->ABaraaapa": 0.761333703994751,
-          "ABaraaap->ABaraaapp": 0.761333703994751,
-          "ABaraapa->ABaraapaa": 0.761333703994751,
-          "ABaraapa->ABaraapap": 0.6432212591171265,
-          "ABaraapp->ABaraappa": 0.6432212591171265,
-          "ABaraapp->ABaraappp": 0.761333703994751,
-          "ABarapaa->ABarapaaa": 0.6432212591171265,
-          "ABarapaa->ABarapaap": 0.761333703994751,
-          "ABarapap->ABarapapa": 0.761333703994751,
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-          "ABarappa->ABarappaa": 0.761333703994751,
-          "ABarappa->ABarappap": 0.761333703994751,
-          "ABarappp->ABarapppa": 0.6432212591171265,
-          "ABarappp->ABarapppp": 0.761333703994751,
-          "ABarpaaa->ABarpaaaa": 0.761333703994751,
-          "ABarpaaa->ABarpaaap": 0.6432212591171265,
-          "ABarpaap->ABarpaapa": 0.761333703994751,
-          "ABarpaap->ABarpaapp": 0.761333703994751,
-          "ABarpapa->ABarpapaa": 0.6432212591171265,
-          "ABarpapa->ABarpapap": 0.761333703994751,
-          "ABarpapp->ABarpappa": 0.761333703994751,
-          "ABarpapp->ABarpappp": 0.761333703994751,
-          "ABarppaa->ABarppaaa": 0.6432212591171265,
-          "ABarppaa->ABarppaap": 0.6432212591171265,
-          "ABarppap->ABarppapa": 0.6432212591171265,
-          "ABarppap->ABarppapp": 0.6432212591171265,
-          "ABarpppa->ABarpppaa": 0.6432212591171265,
-          "ABarpppa->ABarpppap": 0.761333703994751,
-          "ABarpppp->ABarppppa": 0.761333703994751,
-          "ABarpppp->ABarppppp": 0.761333703994751,
-          "ABplaaaa->ABplaaaaa": 0.761333703994751,
-          "ABplaaaa->ABplaaaap": 0.761333703994751,
-          "ABplaaap->ABplaaapa": 0.6432212591171265,
-          "ABplaaap->ABplaaapp": 0.6432212591171265,
-          "ABplaapa->ABplaapaa": 0.761333703994751,
-          "ABplaapa->ABplaapap": 0.761333703994751,
-          "ABplaapp->ABplaappa": 0.6432212591171265,
-          "ABplaapp->ABplaappp": 0.761333703994751,
-          "ABplapaa->ABplapaaa": 0.761333703994751,
-          "ABplapaa->ABplapaap": 0.761333703994751,
-          "ABplapap->ABplapapa": 0.761333703994751,
-          "ABplapap->ABplapapp": 0.6432212591171265,
-          "ABplappa->ABplappaa": 0.6432212591171265,
-          "ABplappa->ABplappap": 0.761333703994751,
-          "ABplappp->ABplapppa": 0.761333703994751,
-          "ABplappp->ABplapppp": 0.6432212591171265,
-          "ABplpaaa->ABplpaaaa": 0.761333703994751,
-          "ABplpaaa->ABplpaaap": 0.5572793483734131,
-          "ABplpaap->ABplpaapa": 0.761333703994751,
-          "ABplpaap->ABplpaapp": 0.6432212591171265,
-          "ABplpapa->ABplpapaa": 0.761333703994751,
-          "ABplpapa->ABplpapap": 0.761333703994751,
-          "ABplpapp->ABplpappa": 0.761333703994751,
-          "ABplpapp->ABplpappp": 0.761333703994751,
-          "ABplppaa->ABplppaaa": 0.5572793483734131,
-          "ABplppaa->ABplppaap": 0.761333703994751,
-          "ABplppap->ABplppapa": 0.761333703994751,
-          "ABplppap->ABplppapp": 0.761333703994751,
-          "ABplpppa->ABplpppaa": 0.761333703994751,
-          "ABplpppa->ABplpppap": 0.5572793483734131,
-          "ABplpppp->ABplppppa": 0.761333703994751,
-          "ABplpppp->ABplppppp": 0.761333703994751,
-          "ABpraaaa->ABpraaaaa": 0.5572793483734131,
-          "ABpraaaa->ABpraaaap": 0.5572793483734131,
-          "ABpraaap->ABpraaapa": 0.761333703994751,
-          "ABpraaap->ABpraaapp": 0.761333703994751,
-          "ABpraapa->ABpraapaa": 0.761333703994751,
-          "ABpraapa->ABpraapap": 0.761333703994751,
-          "ABpraapp->ABpraappa": 0.761333703994751,
-          "ABpraapp->ABpraappp": 0.761333703994751,
-          "ABprapaa->ABprapaaa": 0.761333703994751,
-          "ABprapaa->ABprapaap": 0.761333703994751,
-          "ABprapap->ABprapapa": 0.761333703994751,
-          "ABprapap->ABprapapp": 0.761333703994751,
-          "ABprappa->ABprappaa": 0.5572793483734131,
-          "ABprappa->ABprappap": 0.761333703994751,
-          "ABprappp->ABprapppa": 0.761333703994751,
-          "ABprappp->ABprapppp": 0.761333703994751,
-          "ABprpaaa->ABprpaaaa": 0.761333703994751,
-          "ABprpaaa->ABprpaaap": 0.761333703994751,
-          "ABprpaap->ABprpaapa": 0.761333703994751,
-          "ABprpaap->ABprpaapp": 0.5572793483734131,
-          "ABprpapa->ABprpapaa": 0.761333703994751,
-          "ABprpapa->ABprpapap": 0.761333703994751,
-          "ABprpapp->ABprpappa": 0.761333703994751,
-          "ABprpapp->ABprpappp": 0.761333703994751,
-          "ABprppaa->ABprppaaa": 0.5572793483734131,
-          "ABprppaa->ABprppaap": 0.761333703994751,
-          "ABprppap->ABprppapa": 0.761333703994751,
-          "ABprppap->ABprppapp": 0.761333703994751,
-          "ABprpppa->ABprpppaa": 0.6432212591171265,
-          "ABprpppa->ABprpppap": 0.6432212591171265,
-          "ABprpppp->ABprppppa": 0.6432212591171265,
-          "ABprpppp->ABprppppp": 0.6432212591171265,
-          "MSaaaa->MSaaaaa": 0.761333703994751,
-          "MSaaaa->MSaaaap": 0.761333703994751,
-          "MSaaap->MSaaapa": 0.5572793483734131,
-          "MSaaap->MSaaapp": 0.5572793483734131,
-          "MSaapa->MSaapaa": 0.761333703994751,
-          "MSaapa->MSaapap": 0.761333703994751,
-          "MSaapp->MSaappa": 0.761333703994751,
-          "MSaapp->MSaappp": 0.5572793483734131,
-          "MSapaa->MSapaaa": 0.761333703994751,
-          "MSapaa->MSapaap": 0.761333703994751,
-          "MSapap->MSapapa": 0.761333703994751,
-          "MSapap->MSapapp": 0.5572793483734131,
-          "MSappa->MSappaa": 0.761333703994751,
-          "MSappa->MSappap": 0.761333703994751,
-          "MSappp->MSapppa": 0.6432212591171265,
-          "MSappp->MSapppp": 0.6432212591171265,
-          "MSpaaa->MSpaaaa": 0.5572793483734131,
-          "MSpaaa->MSpaaap": 0.6432212591171265,
-          "MSpaap->MSpaapa": 0.761333703994751,
-          "MSpaap->MSpaapp": 0.761333703994751,
-          "MSpapa->MSpapaa": 0.6432212591171265,
-          "MSpapa->MSpapap": 0.5572793483734131,
-          "MSpapp->MSpappa": 0.6432212591171265,
-          "MSpapp->MSpappp": 0.5572793483734131,
-          "MSppaa->MSppaaa": 0.6432212591171265,
-          "MSppaa->MSppaap": 0.6432212591171265,
-          "MSppap->MSppapa": 0.6432212591171265,
-          "MSppap->MSppapp": 0.6432212591171265,
-          "MSpppa->MSpppaa": 0.6432212591171265,
-          "MSpppa->MSpppap": 0.6432212591171265,
-          "MSpppp->MSppppa": 0.761333703994751,
-          "MSpppp->MSppppp": 0.761333703994751,
-          "Eal->Eala": 0.6432212591171265,
-          "Eal->Ealp": 0.6432212591171265,
-          "Ear->Eara": 0.6432212591171265,
-          "Ear->Earp": 0.6432212591171265,
-          "Epl->Epla": 0.5572793483734131,
-          "Epl->Eplp": 0.5572793483734131,
-          "Epr->Epra": 0.6432212591171265,
-          "Epr->Eprp": 0.6432212591171265,
-          "Caaa->Caaaa": 0.5572793483734131,
-          "Caaa->Caaap": 0.5572793483734131,
-          "Caap->Caapa": 0.6432212591171265,
-          "Caap->Caapp": 0.6432212591171265,
-          "Capa->Capaa": 0.761333703994751,
-          "Capa->Capap": 0.6432212591171265,
-          "Capp->Cappa": 0.6432212591171265,
-          "Capp->Cappp": 0.6432212591171265,
-          "Cpaa->Cpaaa": 0.5572793483734131,
-          "Cpaa->Cpaap": 0.6432212591171265,
-          "Cpap->Cpapa": 0.6432212591171265,
-          "Cpap->Cpapp": 0.6432212591171265,
-          "Cppa->Cppaa": 0.5572793483734131,
-          "Cppa->Cppap": 0.5572793483734131,
-          "Cppp->Cpppa": 0.5572793483734131,
-          "Cppp->Cpppp": 0.6432212591171265,
-          "Da->Daa": 0.5572793483734131,
-          "Dap->Dapa": 0.6432212591171265,
-          "Dap->Dapp": 0.5572793483734131,
-          "Dp->Dpa": 0.5572793483734131,
-          "Dpp->Dppa": 0.6432212591171265,
-          "Dpp->Dppp": 0.6432212591171265
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-      }
-    ]
-  },
-  "rnai_embryo": {
-    "filename": "CD030906_dyf7red.npz",
-    "timesteps": [
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-      60,
-      90,
-      120,
-      150,
-      180
-    ],
-    "data": [
-      {
-        "timestep": 30,
-        "attentions": {
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-          "ABal->ABalp": 1.0,
-          "ABar->ABara": 1.0,
-          "ABar->ABarp": 0.9123597741127014,
-          "ABpl->ABpla": 0.9123597741127014,
-          "ABpl->ABplp": 0.9123597741127014,
-          "ABpr->ABpra": 0.9123597741127014,
-          "ABpr->ABprp": 0.9123597741127014,
-          "MS->MSa": 0.9123597741127014,
-          "MS->MSp": 0.9123597741127014,
-          "E->Ea": 1.0,
-          "E->Ep": 0.9123597741127014
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-      },
-      {
-        "timestep": 60,
-        "attentions": {
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-          "ABarpa->ABarapa": 1.0,
-          "ABala->ABalaa": 0.9123597741127014,
-          "ABala->ABalap": 0.9123597741127014,
-          "ABalp->ABalpa": 0.9123597741127014,
-          "ABalp->ABalpp": 0.9123597741127014,
-          "ABara->ABaraa": 0.9123597741127014,
-          "ABarap->ABarapa": 0.9123597741127014,
-          "ABarap->ABarapp": 0.9123597741127014,
-          "ABarp->ABarpa": 0.9123597741127014,
-          "ABarp->ABarpp": 0.9123597741127014,
-          "ABplaa->ABplaaa": 0.9123597741127014,
-          "ABplaa->ABplaap": 0.9123597741127014,
-          "ABplap->ABplapa": 0.9123597741127014,
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-          "ABplp->ABplpa": 0.9123597741127014,
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-          "ABalapp->ABalappp": 0.8292930126190186,
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-          "ABalpap->ABalpapa": 0.8292930126190186,
-          "ABalpap->ABalpapp": 0.761333703994751,
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-          "ABplaaa->ABplaaaa": 0.8292930126190186,
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-          "ABplaap->ABplaapa": 0.8292930126190186,
-          "ABplaapp->ABplaappa": 0.8292930126190186,
-          "ABplaapp->ABplaappp": 0.8292930126190186,
-          "ABplapa->ABplapaa": 0.8292930126190186,
-          "ABplapa->ABplapap": 0.8292930126190186,
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-          "ABplapp->ABplappp": 0.9123597741127014,
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-          "ABplpaa->ABplpaap": 0.9123597741127014,
-          "ABplpap->ABplpapa": 0.9123597741127014,
-          "ABplpap->ABplpapp": 0.9123597741127014,
-          "ABplppa->ABplppaa": 0.8292930126190186,
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-          "ABplppp->ABplpppa": 0.8292930126190186,
-          "ABplppp->ABplpppp": 0.9123597741127014,
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-          "ABpraap->ABpraapp": 0.9123597741127014,
-          "ABprapa->ABprapaa": 0.761333703994751,
-          "ABprapa->ABprapap": 0.761333703994751,
-          "ABprapp->ABprappa": 0.9123597741127014,
-          "ABprapp->ABprappp": 0.9123597741127014,
-          "ABprpaa->ABprpaaa": 0.8292930126190186,
-          "ABprpaa->ABprpaap": 0.9123597741127014,
-          "ABprpap->ABprpapa": 0.8292930126190186,
-          "ABprpap->ABprpapp": 0.8292930126190186,
-          "ABprppa->ABprppaa": 0.8292930126190186,
-          "ABprppa->ABprppap": 0.9123597741127014,
-          "ABprppp->ABprpppa": 0.8292930126190186,
-          "ABprppp->ABprpppp": 0.9123597741127014,
-          "MSaaa->MSaaaa": 0.8292930126190186,
-          "MSaaa->MSaaap": 0.8292930126190186,
-          "MSaap->MSaapa": 0.8292930126190186,
-          "MSaap->MSaapp": 0.8292930126190186,
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-          "MSapa->MSapap": 0.8292930126190186,
-          "MSapp->MSappa": 0.8292930126190186,
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-          "MSppa->MSppaa": 0.9123597741127014,
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-          "MSppp->MSpppa": 0.9123597741127014,
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-          "Eal->Eala": 0.9123597741127014,
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-          "MSaapaa->MSaapaap": 0.5572793483734131,
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-          "MSapaa->MSapaaa": 0.5572793483734131,
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-          "MSappp->MSapppp": 0.4652247428894043,
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-          "MSppap->MSppapp": 0.6432212591171265,
-          "MSpppa->MSpppaa": 0.6432212591171265,
-          "MSpppa->MSpppap": 0.6432212591171265,
-          "MSpppp->MSppppa": 0.6432212591171265,
-          "MSpppp->MSppppp": 0.6432212591171265,
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-          "Eala->Ealap": 0.40993422269821167,
-          "Ealp->Ealpa": 0.5572793483734131,
-          "Ealp->Ealpp": 0.5572793483734131,
-          "Eara->Earaa": 0.5572793483734131,
-          "Eara->Earap": 0.40993422269821167,
-          "Earp->Earpa": 0.5572793483734131,
-          "Earp->Earpp": 0.5572793483734131,
-          "Epla->Eplaa": 0.5572793483734131,
-          "Epla->Eplap": 0.40993422269821167,
-          "Epl->Eplp": 0.40993422269821167,
-          "Epra->Epraa": 0.5572793483734131,
-          "Epra->Eprap": 0.5572793483734131,
-          "Eprp->Eprpa": 0.40993422269821167,
-          "Eprp->Eprpp": 0.5572793483734131,
-          "Caaaa->Caaaaa": 0.40993422269821167,
-          "Caaaa->Caaaap": 0.5572793483734131,
-          "Caaap->Caaapa": 0.40993422269821167,
-          "Caaap->Caaapp": 0.6432212591171265,
-          "Caap->Caapa": 0.6432212591171265,
-          "Caap->Caapp": 0.40993422269821167,
-          "Capa->Capaa": 0.6432212591171265,
-          "Capa->Capap": 0.40993422269821167,
-          "Capp->Cappa": 0.6432212591171265,
-          "Capp->Cappp": 0.40993422269821167,
-          "Cpaaa->Cpaaaa": 0.40993422269821167,
-          "Cpaaa->Cpaaap": 0.6432212591171265,
-          "Cpaap->Cpaapa": 0.40993422269821167,
-          "Cpaap->Cpaapp": 0.40993422269821167,
-          "Cpapa->Cpapaa": 0.5572793483734131,
-          "Cpapa->Cpapap": 0.40993422269821167,
-          "Cpapp->Cpappd": 0.5572793483734131,
-          "Cpapp->Cpappv": 0.40993422269821167,
-          "Cppa->Cppaa": 0.5572793483734131,
-          "Cppa->Cppap": 0.5572793483734131,
-          "Cppp->Cpppa": 0.5572793483734131,
-          "Cppp->Cpppp": 0.40993422269821167,
-          "Daa->Daaa": 0.5572793483734131,
-          "Daa->Daap": 0.5572793483734131,
-          "Dap->Dapa": 0.5572793483734131,
-          "Dap->Dapp": 0.5572793483734131,
-          "Dpa->Dpaa": 0.5572793483734131,
-          "Dpa->Dpap": 0.5572793483734131,
-          "Dpp->Dppa": 0.5572793483734131,
-          "Dpp->Dppp": 0.5572793483734131
-        }
-      }
-    ]
-  }
-}
\ No newline at end of file
diff --git a/Spatio-Temporal-Evolution/dashboard/fate_dashboard.template.html b/Spatio-Temporal-Evolution/dashboard/fate_dashboard.template.html
new file mode 100644
index 0000000..144596a
--- /dev/null
+++ b/Spatio-Temporal-Evolution/dashboard/fate_dashboard.template.html
@@ -0,0 +1,454 @@
+<style>
+  /* ---- ESTGEL cell-fate viewer: committed dark microscopy instrument ---- */
+  :root{
+    --bg:#0a0d13; --panel:#11151d; --panel-2:#151b26; --stage:#05070b;
+    --line:#222a38; --line-soft:#1a212c;
+    --ink:#e8eef7; --muted:#93a0b4; --faint:#5c6879;
+    --accent:#7cc4ff; --accent-dim:#2b4a63;
+    --good:#5ec27a; --warn:#e6b23c; --bad:#e56a6a;
+    --f-neuron:#f4b942; --f-muscle:#ef5a5a; --f-hypodermis:#2fc3b4;
+    --f-pharynx:#b57be8; --f-intestine:#6cc24a; --f-glia:#4d9de0;
+    --f-germline:#e879c0; --f-excretory:#d99a4e; --f-coelomocyte:#9aa7bd;
+    --f-death:#5b6472; --f-other:#7a8699; --f-mixed:#3d4757; --f-unknown:#3d4757;
+    --mono:ui-monospace,"Cascadia Code","SF Mono",Consolas,monospace;
+    --sans:system-ui,"Segoe UI",Roboto,Helvetica,Arial,sans-serif;
+    --r:12px; --r-sm:8px;
+  }
+  *{box-sizing:border-box}
+  body{margin:0;background:
+      radial-gradient(1200px 700px at 78% -10%,#101827 0%,transparent 55%),
+      var(--bg);
+    color:var(--ink);font-family:var(--sans);line-height:1.45;
+    -webkit-font-smoothing:antialiased;}
+  .wrap{max-width:1320px;margin:0 auto;padding:26px 22px 60px;}
+  a{color:var(--accent);text-decoration:none}
+
+  .top{display:flex;justify-content:space-between;align-items:flex-end;gap:24px;
+    flex-wrap:wrap;padding-bottom:18px;border-bottom:1px solid var(--line);}
+  .brand{display:flex;flex-direction:column;gap:7px}
+  .eyebrow{font-family:var(--mono);font-size:11px;letter-spacing:.22em;
+    text-transform:uppercase;color:var(--accent);}
+  h1{font-size:26px;font-weight:650;margin:0;letter-spacing:-.01em;text-wrap:balance}
+  .sub{color:var(--muted);font-size:13.5px;max-width:60ch}
+  .chips{display:flex;gap:10px;flex-wrap:wrap}
+  .chip{background:var(--panel);border:1px solid var(--line);border-radius:var(--r-sm);
+    padding:9px 13px;display:flex;flex-direction:column;gap:2px;min-width:78px}
+  .chip .k{font-family:var(--mono);font-size:10px;letter-spacing:.1em;text-transform:uppercase;color:var(--faint)}
+  .chip .v{font-family:var(--mono);font-size:19px;font-weight:600;font-variant-numeric:tabular-nums}
+
+  .grid{display:grid;grid-template-columns:1fr 312px;gap:16px;margin-top:18px}
+  .card{background:var(--panel);border:1px solid var(--line);border-radius:var(--r);overflow:hidden}
+  .card h2{font-size:12px;letter-spacing:.14em;text-transform:uppercase;color:var(--muted);
+    margin:0;padding:14px 16px;border-bottom:1px solid var(--line-soft);font-weight:600;
+    display:flex;justify-content:space-between;align-items:center;gap:10px}
+  .card h2 .note{font-family:var(--mono);font-size:10px;letter-spacing:.04em;color:var(--faint);text-transform:none}
+
+  .stage-card{display:flex;flex-direction:column}
+  .stage{position:relative;background:
+      radial-gradient(circle at 50% 42%,#0a121d 0%,var(--stage) 70%);
+    aspect-ratio:16/11;min-height:340px}
+  #view{position:absolute;inset:0;width:100%;height:100%;display:block;cursor:grab;touch-action:none}
+  #view:active{cursor:grabbing}
+  .hint{position:absolute;left:14px;bottom:12px;font-family:var(--mono);font-size:10.5px;
+    color:var(--faint);letter-spacing:.03em;pointer-events:none}
+  .frame-tag{position:absolute;right:14px;top:12px;font-family:var(--mono);font-size:11px;
+    color:var(--muted);background:#0009;border:1px solid var(--line);border-radius:6px;padding:4px 9px}
+  .tooltip{position:absolute;pointer-events:none;z-index:5;background:#0c1219ee;border:1px solid var(--line);
+    border-radius:7px;padding:7px 9px;font-family:var(--mono);font-size:11px;opacity:0;transition:opacity .1s;
+    transform:translate(-50%,-118%);white-space:nowrap;box-shadow:0 6px 22px #000a}
+  .tooltip .tn{color:var(--ink);font-weight:600}
+  .tooltip .tf{font-size:10px}
+
+  .transport{display:flex;align-items:center;gap:14px;padding:12px 16px;border-top:1px solid var(--line-soft);flex-wrap:wrap}
+  .play{width:38px;height:38px;border-radius:50%;border:1px solid var(--line);background:var(--panel-2);
+    color:var(--ink);cursor:pointer;display:grid;place-items:center;flex:none;transition:.15s;font-size:12px}
+  .play:hover{border-color:var(--accent-dim);color:var(--accent)}
+  .scrub{flex:1;min-width:160px;display:flex;flex-direction:column;gap:5px}
+  .scrub input{width:100%;accent-color:var(--accent);cursor:pointer}
+  .scrub .ticks{display:flex;justify-content:space-between;font-family:var(--mono);font-size:9.5px;color:var(--faint)}
+  .tlabel{font-family:var(--mono);font-size:12px;color:var(--muted);min-width:82px;text-align:right}
+  .tlabel b{color:var(--ink)}
+  .toggles{display:flex;gap:8px}
+  .tg{font-family:var(--mono);font-size:10.5px;letter-spacing:.04em;text-transform:uppercase;
+    border:1px solid var(--line);background:var(--panel-2);color:var(--muted);border-radius:20px;
+    padding:6px 11px;cursor:pointer;display:flex;align-items:center;gap:6px;transition:.14s;user-select:none}
+  .tg:hover{border-color:var(--accent-dim)}
+  .tg .sw{width:8px;height:8px;border-radius:50%;background:var(--faint)}
+  .tg.on{color:var(--ink);border-color:var(--accent-dim)}
+  .tg.on .sw{background:var(--accent);box-shadow:0 0 8px var(--accent)}
+  .tg.miss.on .sw{background:var(--warn);box-shadow:0 0 8px var(--warn)}
+
+  .rail{display:flex;flex-direction:column;gap:16px}
+  .legend{padding:10px}
+  .lg{display:flex;align-items:center;gap:10px;padding:8px 9px;border-radius:var(--r-sm);cursor:pointer;
+    transition:.12s;border:1px solid transparent}
+  .lg:hover{background:var(--panel-2)}
+  .lg.off{opacity:.34}
+  .lg .dot{width:12px;height:12px;border-radius:3px;flex:none;box-shadow:0 0 10px -1px currentColor}
+  .lg .nm{flex:1;font-size:13px;text-transform:capitalize}
+  .lg .ct{font-family:var(--mono);font-size:12px;color:var(--muted);font-variant-numeric:tabular-nums}
+  .lg .bar{height:3px;border-radius:2px;background:currentColor;margin-top:3px;opacity:.5}
+
+  .inspect{padding:14px 16px;min-height:150px}
+  .insp-empty{color:var(--faint);font-size:12.5px;font-family:var(--mono);padding:14px 0;text-align:center}
+  .insp-name{font-family:var(--mono);font-size:17px;font-weight:600;letter-spacing:.02em}
+  .insp-row{display:flex;justify-content:space-between;gap:12px;padding:7px 0;border-bottom:1px solid var(--line-soft);
+    font-size:12.5px;align-items:center}
+  .insp-row .k{color:var(--muted)}
+  .insp-row .v{font-family:var(--mono);font-variant-numeric:tabular-nums}
+  .tag{display:inline-flex;align-items:center;gap:6px;font-size:12px;padding:3px 9px;border-radius:20px;
+    text-transform:capitalize;font-weight:500}
+  .tag .dot{width:8px;height:8px;border-radius:50%}
+  .verdict{font-family:var(--mono);font-size:11px;padding:2px 8px;border-radius:5px}
+  .verdict.ok{color:var(--good);background:#5ec27a1a} .verdict.no{color:var(--bad);background:#e56a6a1a}
+  .meter{height:6px;border-radius:4px;background:var(--panel-2);overflow:hidden;margin-top:5px}
+  .meter i{display:block;height:100%;background:var(--accent)}
+
+  .section-h{margin:34px 2px 4px;display:flex;align-items:baseline;gap:14px;flex-wrap:wrap}
+  .section-h h2{font-size:18px;font-weight:620;margin:0;letter-spacing:-.01em}
+  .section-h p{color:var(--muted);font-size:13px;margin:0}
+  .xgrid{display:grid;grid-template-columns:1.05fr 1fr;gap:16px;margin-top:14px}
+  .panel-b{padding:16px}
+  .headline{display:flex;gap:18px;align-items:center;flex-wrap:wrap;margin-bottom:14px}
+  .big{font-family:var(--mono);font-size:30px;font-weight:600;font-variant-numeric:tabular-nums;line-height:1}
+  .big.flip{color:var(--warn)}
+  .headline .lab{font-size:12px;color:var(--muted);max-width:22ch}
+  .arrow{font-family:var(--mono);color:var(--faint);font-size:22px}
+
+  .bars{display:flex;flex-direction:column;gap:9px}
+  .brow{display:grid;grid-template-columns:78px 1fr 42px;align-items:center;gap:10px;font-size:12px}
+  .brow .bl{text-transform:capitalize;color:var(--muted)}
+  .track{height:9px;background:var(--panel-2);border-radius:5px;overflow:hidden;position:relative}
+  .track i{display:block;height:100%;border-radius:5px}
+  .brow .bv{font-family:var(--mono);font-size:11.5px;text-align:right;font-variant-numeric:tabular-nums;color:var(--muted)}
+
+  table.heat{border-collapse:separate;border-spacing:3px;width:100%;font-family:var(--mono);font-size:11px}
+  table.heat th{color:var(--faint);font-weight:500;font-size:10px;padding:3px;text-transform:capitalize;text-align:center}
+  table.heat td.rl{color:var(--muted);text-align:right;padding-right:6px;text-transform:capitalize;font-size:10.5px}
+  table.heat td.c{text-align:center;border-radius:5px;padding:7px 4px;color:#dfe8f4;font-variant-numeric:tabular-nums}
+  .cap{color:var(--faint);font-size:11px;margin-top:12px;font-family:var(--mono)}
+
+  .metarow{display:grid;grid-template-columns:1fr 1fr;gap:16px}
+  svg.spark{width:100%;height:132px;display:block}
+  .lgi{display:flex;gap:16px;font-family:var(--mono);font-size:10.5px;color:var(--muted);margin-top:6px}
+  .lgi span{display:flex;align-items:center;gap:5px} .lgi i{width:14px;height:2.5px;border-radius:2px;display:inline-block}
+
+  .foot{margin-top:34px;padding-top:16px;border-top:1px solid var(--line);color:var(--faint);
+    font-size:12px;font-family:var(--mono);display:flex;justify-content:space-between;gap:16px;flex-wrap:wrap}
+
+  @media(max-width:940px){.grid{grid-template-columns:1fr}.xgrid,.metarow{grid-template-columns:1fr}}
+  @media(prefers-reduced-motion:reduce){*{animation:none!important;transition:none!important}}
+</style>
+
+<div class="wrap">
+  <header class="top">
+    <div class="brand">
+      <span class="eyebrow">ESTGEL · DevoGraph</span>
+      <h1>Cell-fate map of a <i>C.&nbsp;elegans</i> embryo</h1>
+      <p class="sub">A spatio-temporal graph network predicts each cell's terminal tissue from its
+        position, size and lineage dynamics — never its name. Play development forward, watch cells
+        divide, and inspect what drives each call.</p>
+    </div>
+    <div class="chips" id="chips"></div>
+  </header>
+
+  <div class="grid">
+    <section class="card stage-card">
+      <h2>3D embryo · predicted fate <span class="note" id="emb-name"></span></h2>
+      <div class="stage">
+        <canvas id="view"></canvas>
+        <div class="frame-tag" id="frameTag">t = 0 min</div>
+        <div class="hint">drag to rotate · scroll to zoom · click a cell</div>
+        <div class="tooltip" id="tip"></div>
+      </div>
+      <div class="transport">
+        <button class="play" id="play" aria-label="Play developmental time">▶</button>
+        <div class="scrub">
+          <input type="range" id="slider" min="0" max="29" value="0" step="0.01">
+          <div class="ticks" id="ticks"></div>
+        </div>
+        <div class="toggles">
+          <button class="tg contacts on" id="tgEdges"><span class="sw"></span>contacts</button>
+          <button class="tg miss on" id="tgMiss"><span class="sw"></span>misses</button>
+        </div>
+        <div class="tlabel">t = <b id="tmin">0</b> min</div>
+      </div>
+    </section>
+
+    <aside class="rail">
+      <div class="card">
+        <h2>Tissue fates <span class="note">click to isolate</span></h2>
+        <div class="legend" id="legend"></div>
+      </div>
+      <div class="card">
+        <h2>Cell inspector</h2>
+        <div class="inspect" id="inspect">
+          <div class="insp-empty">Hover or click a cell in the embryo</div>
+        </div>
+      </div>
+    </aside>
+  </div>
+
+  <div class="section-h">
+    <h2>What drives the prediction</h2>
+    <p>Attention weights saturate, so importance is measured by perturbation — remove an input and watch the call move.</p>
+  </div>
+
+  <div class="xgrid">
+    <section class="card">
+      <h2>Do interactions matter? · graph ablation</h2>
+      <div class="panel-b">
+        <div class="headline">
+          <div><div class="big" id="accFull">—</div><div class="lab">accuracy, full graph</div></div>
+          <div class="arrow">→</div>
+          <div><div class="big" id="accNo" style="color:var(--bad)">—</div><div class="lab">edges removed</div></div>
+          <div style="margin-left:auto;text-align:right">
+            <div class="big flip" id="flip">—</div><div class="lab">of fates flip<br>without contacts</div></div>
+        </div>
+        <div class="bars" id="ablBars"></div>
+        <div class="cap">Removing every cell–cell edge and re-predicting. Confidence drop per tissue → contacts carry real fate signal.</div>
+      </div>
+    </section>
+
+    <section class="card">
+      <h2>Which features drive each fate · occlusion</h2>
+      <div class="panel-b">
+        <div id="occHeat"></div>
+        <div class="cap">Confidence lost when a feature is mean-imputed. Warmer = the feature supports that tissue's call.</div>
+      </div>
+    </section>
+
+    <section class="card">
+      <h2>Tissue-to-tissue contacts</h2>
+      <div class="panel-b">
+        <div id="contactHeat"></div>
+        <div class="cap">How often the model sees each tissue in contact with another (log scale). Diagonal = like-fate clustering.</div>
+      </div>
+    </section>
+
+    <section class="card">
+      <h2>Model performance</h2>
+      <div class="panel-b">
+        <div class="metarow">
+          <div>
+            <svg class="spark" id="curve" viewBox="0 0 260 132" preserveAspectRatio="none"></svg>
+            <div class="lgi"><span><i style="background:var(--accent)"></i>val accuracy</span><span><i style="background:var(--f-neuron)"></i>macro-F1</span></div>
+          </div>
+          <div>
+            <div class="bars" id="recallBars"></div>
+          </div>
+        </div>
+      </div>
+    </section>
+  </div>
+
+  <div class="foot">
+    <span id="footL">ESTGEL node classifier · EPIC lineage data</span>
+    <span>fate labels from the invariant C. elegans lineage · trained on held-out embryos</span>
+  </div>
+</div>
+
+<script id="fate-data" type="application/json">__FATE_DATA__</script>
+<script>
+(function(){
+  const DATA = JSON.parse(document.getElementById('fate-data').textContent);
+  const css = getComputedStyle(document.documentElement);
+  const colorCache={};
+  const colorOf = f => colorCache[f] || (colorCache[f]=(css.getPropertyValue('--f-'+f).trim()||'#7a8699'));
+
+  /* ---------- header chips ---------- */
+  const hist=(DATA.metrics.history||[]), last=hist[hist.length-1]||{};
+  const chips=[['cells',DATA.n_cells],['val acc',last.val_acc!=null?(last.val_acc*100).toFixed(0)+'%':'—'],
+    ['macro-F1',last.val_macro_f1!=null?last.val_macro_f1.toFixed(2):'—'],
+    ['tissues',new Set(DATA.cells.map(c=>c.fate)).size]];
+  document.getElementById('chips').innerHTML=chips.map(([k,v])=>`<div class="chip"><span class="k">${k}</span><span class="v">${v}</span></div>`).join('');
+  document.getElementById('emb-name').textContent=DATA.embryo;
+  document.getElementById('footL').textContent='ESTGEL node classifier · '+DATA.embryo;
+
+  /* ---------- legend ---------- */
+  const counts={}; DATA.cells.forEach(c=>counts[c.fate]=(counts[c.fate]||0)+1);
+  const fates=Object.keys(counts).sort((a,b)=>counts[b]-counts[a]);
+  const maxCt=Math.max(...Object.values(counts)), hidden=new Set();
+  const legend=document.getElementById('legend');
+  legend.innerHTML=fates.map(f=>`
+    <div class="lg" data-f="${f}" style="color:${colorOf(f)}">
+      <span class="dot" style="background:${colorOf(f)}"></span>
+      <span style="flex:1"><span style="display:flex;justify-content:space-between">
+        <span class="nm" style="color:var(--ink)">${f}</span><span class="ct">${counts[f]}</span></span>
+        <span class="bar" style="width:${Math.max(8,counts[f]/maxCt*100)}%;display:block"></span></span></div>`).join('');
+  legend.querySelectorAll('.lg').forEach(el=>el.onclick=()=>{
+    const f=el.dataset.f; hidden.has(f)?(hidden.delete(f),el.classList.remove('off')):(hidden.add(f),el.classList.add('off'));});
+
+  /* ---------- 3D engine ---------- */
+  const cv=document.getElementById('view'), ctx=cv.getContext('2d');
+  const cells=DATA.cells, frames=DATA.frames, edges=DATA.edges||[], NF=frames.length;
+  let yaw=0.6, pitch=-0.35, zoom=1, dragging=false, autoRot=true, sel=-1, hover=-1;
+  let lx=0,ly=0, dpr=Math.min(window.devicePixelRatio||1,2);
+  let t=0, playing=false, speed=0.5;
+  let showEdges=true, showMiss=true;
+
+  let cx=0,cy=0,cz=0,nc=0;
+  cells.forEach(c=>{const p=c.pos[NF-1]||c.pos.find(Boolean);if(p){cx+=p[0];cy+=p[1];cz+=p[2];nc++;}});
+  cx/=nc;cy/=nc;cz/=nc;
+  let sp=0,n2=0; cells.forEach(c=>c.pos.forEach(p=>{if(p){sp+=(p[0]-cx)**2+(p[1]-cy)**2+(p[2]-cz)**2;n2++;}}));
+  const spread=Math.sqrt(sp/n2)||1;
+
+  function resize(){const r=cv.getBoundingClientRect();cv.width=r.width*dpr;cv.height=r.height*dpr;}
+  window.addEventListener('resize',resize);
+
+  function sample(c,tt){
+    const f0=Math.floor(tt), f1=Math.min(f0+1,NF-1), a=tt-f0;
+    const p0=c.pos[f0], p1=c.pos[f1];
+    if(p0&&p1){return {p:[p0[0]+(p1[0]-p0[0])*a,p0[1]+(p1[1]-p0[1])*a,p0[2]+(p1[2]-p0[2])*a],grow:1,alpha:1};}
+    if(!p0&&p1){ let src=p1; if(c.p>=0){const par=cells[c.p].pos[f0]; if(par)src=par;}
+      return {p:[src[0]+(p1[0]-src[0])*a,src[1]+(p1[1]-src[1])*a,src[2]+(p1[2]-src[2])*a],grow:0.25+0.75*a,alpha:0.15+0.85*a,from:src};}
+    if(p0&&!p1){return {p:p0,grow:1-a*0.5,alpha:1-a};}
+    return null;
+  }
+  let rot={};
+  function setRot(){rot={cyw:Math.cos(yaw),syw:Math.sin(yaw),cp:Math.cos(pitch),sp2:Math.sin(pitch)};}
+  function project(P,W,H,R){const {cyw,syw,cp,sp2}=rot; let X=P[0]-cx,Y=P[1]-cy,Z=P[2]-cz;
+    let x1=X*cyw+Z*syw, z1=-X*syw+Z*cyw, y1=Y*cp-z1*sp2, z2=Y*sp2+z1*cp;
+    return {sx:W/2+x1*R, sy:H/2+y1*R, depth:z2};}
+
+  let lastPts=[];
+  function draw(){
+    const W=cv.width,H=cv.height; ctx.clearRect(0,0,W,H); setRot();
+    const R=Math.min(W,H)*0.34*zoom/spread;
+    const f0=Math.min(Math.floor(t),NF-1);
+    const S=new Array(cells.length); const pts=[];
+    for(let i=0;i<cells.length;i++){
+      const c=cells[i]; if(hidden.has(c.fate)){S[i]=null;continue;}
+      const s=sample(c,t); S[i]=s; if(!s)continue;
+      const pr=project(s.p,W,H,R);
+      pts.push({i,sx:pr.sx,sy:pr.sy,depth:pr.depth,s,fate:c.fate,conf:c.conf,sz:c.size,miss:c.correct===false});
+    }
+    const zs=pts.map(p=>p.depth), zmn=zs.length?Math.min(...zs):0, zmx=zs.length?Math.max(...zs):1, zr=(zmx-zmn)||1;
+    if(showEdges && edges[f0]){
+      ctx.lineWidth=Math.max(0.5,0.7*dpr);
+      for(const e of edges[f0]){
+        const si=S[e[0]], sj=S[e[1]]; if(!si||!sj)continue;
+        const a=project(si.p,W,H,R), b=project(sj.p,W,H,R);
+        const tt=((a.depth+b.depth)/2-zmn)/zr;
+        ctx.strokeStyle=`rgba(124,196,255,${0.05+0.14*tt})`;
+        ctx.beginPath();ctx.moveTo(a.sx,a.sy);ctx.lineTo(b.sx,b.sy);ctx.stroke();
+      }
+    }
+    pts.sort((p,q)=>p.depth-q.depth);
+    for(const p of pts){
+      const d=(p.depth-zmn)/zr;
+      const rad=(2.2+(p.sz/45)*3.0)*dpr*(0.6+0.5*d)*zoom*p.s.grow;
+      const col=colorOf(p.fate);
+      if(p.s.from){const fp=project(p.s.from,W,H,R);
+        ctx.strokeStyle=col+'66';ctx.lineWidth=1.1*dpr;
+        ctx.beginPath();ctx.moveTo(fp.sx,fp.sy);ctx.lineTo(p.sx,p.sy);ctx.stroke();}
+      const conf=0.45+0.55*p.conf;
+      ctx.globalAlpha=(0.3+0.6*d)*p.s.alpha*conf;
+      ctx.beginPath();ctx.arc(p.sx,p.sy,rad*2.1,0,7);ctx.fillStyle=col+'22';ctx.fill();
+      ctx.globalAlpha=(0.5+0.5*d)*p.s.alpha*conf;
+      ctx.beginPath();ctx.arc(p.sx,p.sy,rad,0,7);ctx.fillStyle=col;ctx.fill();
+      if(showMiss && p.miss){ctx.globalAlpha=0.9*p.s.alpha;ctx.strokeStyle='#e56a6a';ctx.lineWidth=1.4*dpr;
+        ctx.beginPath();ctx.arc(p.sx,p.sy,rad+3.5*dpr,0,7);ctx.stroke();}
+      if(p.i===sel||p.i===hover){ctx.globalAlpha=1;ctx.lineWidth=1.6*dpr;
+        ctx.strokeStyle=p.i===sel?'#fff':'#ffffffaa';
+        ctx.beginPath();ctx.arc(p.sx,p.sy,rad+3*dpr,0,7);ctx.stroke();}
+    }
+    ctx.globalAlpha=1; lastPts=pts;
+    const tmin=Math.round(frames[f0]+(frames[Math.min(f0+1,NF-1)]-frames[f0])*(t-f0));
+    document.getElementById('frameTag').textContent='t = '+tmin+' min';
+    document.getElementById('tmin').textContent=tmin;
+  }
+
+  function pick(mx,my){let best=-1,bd=13*dpr;
+    for(const p of lastPts){const d=Math.hypot(p.sx-mx*dpr,p.sy-my*dpr);if(d<bd){bd=d;best=p.i;}}return best;}
+
+  cv.addEventListener('pointerdown',e=>{dragging=true;autoRot=false;lx=e.clientX;ly=e.clientY;cv.setPointerCapture(e.pointerId);});
+  cv.addEventListener('pointerup',e=>{
+    if(Math.abs(e.clientX-lx)<3&&Math.abs(e.clientY-ly)<3){const r=cv.getBoundingClientRect();sel=pick(e.clientX-r.left,e.clientY-r.top);inspect(sel);}
+    dragging=false;});
+  cv.addEventListener('pointermove',e=>{const r=cv.getBoundingClientRect();
+    if(dragging){yaw+=(e.clientX-lx)*0.01;pitch=Math.max(-1.4,Math.min(1.4,pitch+(e.clientY-ly)*0.01));lx=e.clientX;ly=e.clientY;}
+    else{const h=pick(e.clientX-r.left,e.clientY-r.top);hover=h;const tip=document.getElementById('tip');
+      if(h>=0){const c=cells[h];tip.style.opacity=1;tip.style.left=(e.clientX-r.left)+'px';tip.style.top=(e.clientY-r.top)+'px';
+        tip.innerHTML=`<div class="tn">${c.name}</div><div class="tf" style="color:${colorOf(c.fate)}">${c.fate} · ${(c.conf*100).toFixed(0)}%${c.correct===false?' · miss':''}</div>`;}
+      else tip.style.opacity=0;}});
+  cv.addEventListener('pointerleave',()=>{hover=-1;document.getElementById('tip').style.opacity=0;});
+  cv.addEventListener('wheel',e=>{e.preventDefault();zoom=Math.max(0.4,Math.min(3.2,zoom*(e.deltaY<0?1.1:0.9)));},{passive:false});
+
+  function inspect(i){const box=document.getElementById('inspect');
+    if(i<0){box.innerHTML='<div class="insp-empty">Hover or click a cell in the embryo</div>';return;}
+    const c=cells[i];
+    const truth=c.true_fate!=null
+      ?`<div class="insp-row"><span class="k">true fate</span><span class="v"><span class="tag" style="background:${colorOf(c.true_fate)}22;color:${colorOf(c.true_fate)}"><span class="dot" style="background:${colorOf(c.true_fate)}"></span>${c.true_fate}</span></span></div>
+        <div class="insp-row"><span class="k">verdict</span><span class="verdict ${c.correct?'ok':'no'}">${c.correct?'correct':'miss'}</span></div>`
+      :`<div class="insp-row"><span class="k">true fate</span><span class="v" style="color:var(--faint)">progenitor / mixed</span></div>`;
+    const par=c.p>=0?cells[c.p].name:'—';
+    box.innerHTML=`<div class="insp-name" style="color:${colorOf(c.fate)}">${c.name}</div>
+      <div class="insp-row"><span class="k">predicted</span><span class="v"><span class="tag" style="background:${colorOf(c.fate)}22;color:${colorOf(c.fate)}"><span class="dot" style="background:${colorOf(c.fate)}"></span>${c.fate}</span></span></div>
+      <div class="insp-row"><span class="k">confidence</span><span class="v">${(c.conf*100).toFixed(1)}%</span></div>
+      <div class="meter"><i style="width:${c.conf*100}%;background:${colorOf(c.fate)}"></i></div>
+      ${truth}
+      <div class="insp-row"><span class="k">parent</span><span class="v">${par}</span></div>
+      <div class="insp-row" style="border:none"><span class="k">born · size</span><span class="v">t${frames[c.b]} · ${c.size}</span></div>`;}
+
+  /* transport */
+  const slider=document.getElementById('slider');
+  slider.max=NF-1;
+  document.getElementById('ticks').innerHTML=frames.map((tt,i)=>(i%6===0||i===NF-1)?`<span>${tt}</span>`:'<span></span>').join('');
+  slider.oninput=()=>{t=+slider.value;};
+  const playBtn=document.getElementById('play');
+  playBtn.onclick=()=>{playing=!playing;playBtn.textContent=playing?'❚❚':'▶';};
+  const tgE=document.getElementById('tgEdges'), tgM=document.getElementById('tgMiss');
+  tgE.onclick=()=>{showEdges=!showEdges;tgE.classList.toggle('on',showEdges);};
+  tgM.onclick=()=>{showMiss=!showMiss;tgM.classList.toggle('on',showMiss);};
+
+  if(matchMedia('(prefers-reduced-motion:reduce)').matches){autoRot=false;}
+  let prev=0;
+  function loop(ts){
+    const dt=Math.min((ts-prev)/1000||0,0.05); prev=ts;
+    if(playing){t+=speed*dt; if(t>=NF-1){t=0;} slider.value=t;}
+    if(autoRot && !dragging){yaw+=0.12*dt;}
+    draw(); requestAnimationFrame(loop);
+  }
+
+  /* ---------- explainability panels ---------- */
+  const sal=DATA.explainability.saliency, inter=DATA.explainability.interactions;
+  const MAJ=['neuron','muscle','hypodermis','pharynx','intestine'];
+  if(sal){
+    document.getElementById('accFull').textContent=(sal.accuracy_full*100).toFixed(0)+'%';
+    document.getElementById('accNo').textContent=(sal.accuracy_no_edges*100).toFixed(0)+'%';
+    document.getElementById('flip').textContent=(sal.prediction_flip_rate_no_edges*100).toFixed(0)+'%';
+    const abl=sal.graph_ablation_confdrop_by_fate||{}, rows=MAJ.filter(f=>f in abl);
+    const amax=Math.max(...rows.map(f=>Math.abs(abl[f])))||1;
+    document.getElementById('ablBars').innerHTML=rows.map(f=>{const v=abl[f],w=Math.abs(v)/amax*100,neg=v<0;
+      return `<div class="brow"><span class="bl">${f}</span><span class="track"><i style="width:${w}%;background:${neg?'var(--faint)':colorOf(f)}"></i></span><span class="bv">${v>=0?'+':''}${v.toFixed(2)}</span></div>`;}).join('');
+    const occ=sal.feature_occlusion_confdrop_by_fate||{}, feats=sal.features||['x','y','z','size','blot'];
+    let allv=[]; MAJ.forEach(f=>occ[f]&&occ[f].forEach(v=>allv.push(Math.abs(v))));
+    const omax=Math.max(...allv,0.001);
+    const hcol=v=>{const q=Math.max(-1,Math.min(1,v/omax));return q>=0?`rgba(244,185,66,${0.12+0.8*q})`:`rgba(90,110,140,${0.12+0.8*-q})`;};
+    let html='<table class="heat"><tr><th></th>'+feats.map(f=>`<th>${f}</th>`).join('')+'</tr>';
+    MAJ.filter(f=>occ[f]).forEach(f=>{html+=`<tr><td class="rl">${f}</td>`+occ[f].map(v=>`<td class="c" style="background:${hcol(v)}">${v.toFixed(2)}</td>`).join('')+'</tr>';});
+    document.getElementById('occHeat').innerHTML=html+'</table>';
+  }
+  if(inter&&inter.contact_counts){
+    const cc=inter.contact_counts, present=inter.tissue_pairs_present.filter(f=>MAJ.includes(f));
+    let mx=0; present.forEach(a=>present.forEach(b=>{const v=(cc[a]||{})[b]||0;if(v>mx)mx=v;}));
+    const lm=Math.log1p(mx)||1, cscale=v=>`rgba(124,196,255,${0.06+0.9*Math.log1p(v)/lm})`;
+    let html='<table class="heat"><tr><th></th>'+present.map(f=>`<th>${f.slice(0,4)}</th>`).join('')+'</tr>';
+    present.forEach(a=>{html+=`<tr><td class="rl">${a}</td>`+present.map(b=>{const v=(cc[a]||{})[b]||0;return `<td class="c" style="background:${cscale(v)}">${v||''}</td>`;}).join('')+'</tr>';});
+    document.getElementById('contactHeat').innerHTML=html+'</table>';
+  }
+  if(hist.length){
+    const W=260,H=132,pad=6,n=hist.length, xs=i=>pad+(n>1?i/(n-1):0.5)*(W-2*pad), yA=v=>H-pad-v*(H-2*pad);
+    const line=(key,col)=>{const d=hist.map((h,i)=>`${i?'L':'M'}${xs(i).toFixed(1)},${yA(h[key]).toFixed(1)}`).join(' ');
+      return `<path d="${d}" fill="none" stroke="${col}" stroke-width="2" stroke-linejoin="round"/><circle cx="${xs(n-1)}" cy="${yA(hist[n-1][key])}" r="3" fill="${col}"/>`;};
+    let grid=''; for(let g=0;g<=1;g+=0.25)grid+=`<line x1="${pad}" y1="${yA(g)}" x2="${W-pad}" y2="${yA(g)}" stroke="#ffffff10"/>`;
+    document.getElementById('curve').innerHTML=grid+line('val_acc',css.getPropertyValue('--accent'))+line('val_macro_f1',css.getPropertyValue('--f-neuron'));
+  }
+  const rec=DATA.metrics.per_class_recall||{}, rkeys=Object.keys(rec).sort((a,b)=>rec[b]-rec[a]);
+  document.getElementById('recallBars').innerHTML='<div style="font-size:11px;color:var(--muted);margin-bottom:8px;text-transform:uppercase;letter-spacing:.1em">Per-class recall</div>'+
+    rkeys.map(f=>`<div class="brow"><span class="bl">${f}</span><span class="track"><i style="width:${rec[f]*100}%;background:${colorOf(f)}"></i></span><span class="bv">${(rec[f]*100).toFixed(0)}%</span></div>`).join('');
+
+  resize(); draw(); requestAnimationFrame(loop);
+})();
+</script>
diff --git a/Spatio-Temporal-Evolution/dashboard/fate_dashboard_data.json b/Spatio-Temporal-Evolution/dashboard/fate_dashboard_data.json
new file mode 100644
index 0000000..46bb290
--- /dev/null
+++ b/Spatio-Temporal-Evolution/dashboard/fate_dashboard_data.json
@@ -0,0 +1 @@
+{"embryo": "CD011505_end1red_bright.csv", "n_cells": 710, "frames": [0, 8, 15, 23, 30, 38, 45, 53, 60, 68, 76, 83, 91, 98, 106, 113, 121, 128, 136, 143, 151, 159, 166, 174, 181, 189, 196, 204, 211, 219], "fate_classes": ["neuron", "muscle", "hypodermis", "pharynx", "intestine", "glia", "germline", "excretory", "coelomocyte", "death", "other", "mixed", "unknown"], "cells": [{"name": "ABa", "fate": "pharynx", "conf": 0.66, "size": 90.0, "b": 0, "p": -1, "pos": [[238.0, 258.0, 14.9], [189.0, 274.0, 15.7], null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null]}, {"name": "ABal", "fate": "pharynx", "conf": 0.745, "size": 81.0, "b": 2, "p": 0, "pos": [null, null, [177.0, 236.0, 15.1], [143.0, 226.0, 17.3], null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null]}, {"name": "ABala", "fate": "neuron", "conf": 0.508, "size": 69.3, "b": 4, "p": 1, "pos": [null, null, null, null, [136.0, 276.0, 16.1], [121.0, 285.0, 15.0], [135.0, 295.0, 13.1], null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], "true_fate": "neuron", "correct": true}, {"name": "ABalaa", "fate": "neuron", "conf": 0.585, "size": 61.7, "b": 7, "p": 2, "pos": [null, null, null, null, null, null, null, [100.0, 271.0, 12.9], [99.0, 261.0, 12.8], [106.0, 276.0, 13.7], null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null]}, {"name": "ABalaaa", "fate": "pharynx", "conf": 0.633, "size": 54.4, "b": 10, "p": 3, "pos": [null, null, null, null, null, null, null, null, null, null, [96.0, 282.0, 13.6], [93.0, 287.0, 14.0], [100.0, 297.0, 13.9], [99.0, 296.0, 13.9], [104.0, 289.0, 13.8], null, null, null, null, null, null, null, null, null, null, null, null, null, null, null]}, {"name": "ABalaaaa", "fate": "neuron", "conf": 0.503, "size": 46.2, "b": 15, "p": 4, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [86.0, 256.0, 11.9], [89.0, 279.0, 14.0], [99.0, 298.0, 13.5], [106.0, 308.0, 17.1], [101.0, 300.0, 18.3], null, null, null, null, null, null, null, null, null, null], "true_fate": "neuron", "correct": true}, {"name": "ABalaaaal", "fate": "pharynx", "conf": 0.822, "size": 38.0, "b": 20, "p": 5, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [98.0, 258.0, 17.1], [95.0, 245.0, 15.4], [101.0, 234.0, 15.2], [103.0, 229.0, 14.4], [108.0, 216.0, 13.1], [100.0, 219.0, 13.8], [103.0, 223.0, 12.4], null, null, null]}, {"name": "ABalaaaala", "fate": "pharynx", "conf": 0.503, "size": 30.7, "b": 27, "p": 6, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, 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"intestine", "correct": true}, {"cell": "Eplaa", "pred_fate": "intestine", "confidence": 0.7261, "true_fate": "intestine", "correct": true}, {"cell": "Eplap", "pred_fate": "intestine", "confidence": 0.7697, "true_fate": "intestine", "correct": true}, {"cell": "Eplp", "pred_fate": "intestine", "confidence": 0.7155, "true_fate": "intestine", "correct": true}, {"cell": "Epr", "pred_fate": "intestine", "confidence": 0.506, "true_fate": "intestine", "correct": true}, {"cell": "Epra", "pred_fate": "hypodermis", "confidence": 0.4268, "true_fate": "intestine", "correct": false}, {"cell": "Epraa", "pred_fate": "muscle", "confidence": 0.6996, "true_fate": "intestine", "correct": false}, {"cell": "Eprap", "pred_fate": "muscle", "confidence": 0.648, "true_fate": "intestine", "correct": false}, {"cell": "Eprp", "pred_fate": "intestine", "confidence": 0.6225, "true_fate": "intestine", "correct": true}, {"cell": "MS", "pred_fate": "pharynx", "confidence": 0.3847}, {"cell": "MSa", "pred_fate": "pharynx", "confidence": 0.406}, {"cell": "MSaa", "pred_fate": "pharynx", "confidence": 0.8085, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaa", "pred_fate": "pharynx", "confidence": 0.9358, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaaa", "pred_fate": "pharynx", "confidence": 0.8788, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaaaa", "pred_fate": "pharynx", "confidence": 0.7418, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaaaaa", "pred_fate": "pharynx", "confidence": 0.8809, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaaaap", "pred_fate": "pharynx", "confidence": 0.9136, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaaap", "pred_fate": "pharynx", "confidence": 0.8164, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaaapa", "pred_fate": "pharynx", "confidence": 0.6581, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaaapp", "pred_fate": "pharynx", "confidence": 0.41, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaap", "pred_fate": "pharynx", "confidence": 0.9031, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaapa", "pred_fate": "pharynx", "confidence": 0.9033, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaapaa", "pred_fate": "pharynx", "confidence": 0.9613, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaapap", "pred_fate": "pharynx", "confidence": 0.8037, "true_fate": "pharynx", "correct": true}, {"cell": "MSaaapp", "pred_fate": "pharynx", "confidence": 0.3655, "true_fate": "intestine", "correct": false}, {"cell": "MSaap", "pred_fate": "pharynx", "confidence": 0.8435}, {"cell": "MSaapa", "pred_fate": "pharynx", "confidence": 0.9197, "true_fate": "pharynx", "correct": true}, {"cell": "MSaapaa", "pred_fate": "pharynx", "confidence": 0.7987, "true_fate": "pharynx", "correct": true}, {"cell": "MSaapaaa", "pred_fate": "pharynx", "confidence": 0.9579, "true_fate": "pharynx", "correct": true}, {"cell": "MSaapaap", "pred_fate": "pharynx", "confidence": 0.7776, "true_fate": "pharynx", "correct": true}, {"cell": "MSaapap", "pred_fate": "pharynx", "confidence": 0.814, "true_fate": "pharynx", "correct": true}, {"cell": "MSaapapa", "pred_fate": "pharynx", "confidence": 0.8082, "true_fate": "pharynx", "correct": true}, {"cell": "MSaapapp", "pred_fate": "muscle", "confidence": 0.3492}, {"cell": "MSaapp", "pred_fate": "pharynx", "confidence": 0.7451, "true_fate": "muscle", "correct": false}, {"cell": "MSaappa", "pred_fate": "muscle", "confidence": 0.4806, "true_fate": "intestine", "correct": false}, {"cell": "MSaappp", "pred_fate": "muscle", "confidence": 0.7155, "true_fate": "muscle", "correct": true}, {"cell": "MSap", "pred_fate": "pharynx", "confidence": 0.4093}, {"cell": "MSapa", "pred_fate": "pharynx", "confidence": 0.6671}, {"cell": "MSapaa", "pred_fate": "pharynx", "confidence": 0.8477}, {"cell": "MSapaaa", "pred_fate": "pharynx", "confidence": 0.7232, "true_fate": "pharynx", "correct": true}, {"cell": "MSapaaaa", "pred_fate": "pharynx", "confidence": 0.581, "true_fate": "pharynx", "correct": true}, {"cell": "MSapaaap", "pred_fate": "pharynx", "confidence": 0.5202, "true_fate": "muscle", "correct": false}, {"cell": "MSapaap", "pred_fate": "pharynx", "confidence": 0.436, "true_fate": "other", "correct": false}, {"cell": "MSapap", "pred_fate": "muscle", "confidence": 0.5164, "true_fate": "muscle", "correct": true}, {"cell": "MSapapa", "pred_fate": "pharynx", "confidence": 0.3059, "true_fate": "coelomocyte", "correct": false}, {"cell": "MSapapaa", "pred_fate": "muscle", "confidence": 0.338, "true_fate": "coelomocyte", "correct": false}, {"cell": "MSapapap", "pred_fate": "muscle", "confidence": 0.4172, "true_fate": "muscle", "correct": true}, {"cell": "MSapapp", "pred_fate": "muscle", "confidence": 0.4904, "true_fate": "muscle", "correct": true}, {"cell": "MSapappa", "pred_fate": "muscle", "confidence": 0.4498, "true_fate": "muscle", "correct": true}, {"cell": "MSapappp", "pred_fate": "muscle", "confidence": 0.3755, "true_fate": "muscle", "correct": true}, {"cell": "MSapp", "pred_fate": "muscle", "confidence": 0.6677, "true_fate": "muscle", "correct": true}, {"cell": "MSappa", "pred_fate": "pharynx", "confidence": 0.4526}, {"cell": "MSappaa", "pred_fate": "muscle", "confidence": 0.3498}, {"cell": "MSappap", "pred_fate": "muscle", "confidence": 0.7139, "true_fate": "muscle", "correct": true}, {"cell": "MSappp", "pred_fate": "muscle", "confidence": 0.6429, "true_fate": "muscle", "correct": true}, {"cell": "MSapppa", "pred_fate": "muscle", "confidence": 0.5132, "true_fate": "muscle", "correct": true}, {"cell": "MSapppp", "pred_fate": "muscle", "confidence": 0.6025, "true_fate": "muscle", "correct": true}, {"cell": "MSp", "pred_fate": "muscle", "confidence": 0.4002}, {"cell": "MSpa", "pred_fate": "pharynx", "confidence": 0.4959, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaa", "pred_fate": "pharynx", "confidence": 0.7684, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaa", "pred_fate": "pharynx", "confidence": 0.7754, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaaa", "pred_fate": "neuron", "confidence": 0.3906, "true_fate": "pharynx", "correct": false}, {"cell": "MSpaaaaa", "pred_fate": "pharynx", "confidence": 0.853, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaaap", "pred_fate": "pharynx", "confidence": 0.9505, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaap", "pred_fate": "pharynx", "confidence": 0.8948, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaapa", "pred_fate": "pharynx", "confidence": 0.7573, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaapp", "pred_fate": "pharynx", "confidence": 0.6295, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaap", "pred_fate": "pharynx", "confidence": 0.8167, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaapa", "pred_fate": "pharynx", "confidence": 0.8085, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaapaa", "pred_fate": "pharynx", "confidence": 0.9076, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaapap", "pred_fate": "pharynx", "confidence": 0.4335}, {"cell": "MSpaapp", "pred_fate": "neuron", "confidence": 0.3601, "true_fate": "pharynx", "correct": false}, {"cell": "MSpap", "pred_fate": "pharynx", "confidence": 0.6564}, {"cell": "MSpapa", "pred_fate": "pharynx", "confidence": 0.8497, "true_fate": "pharynx", "correct": true}, {"cell": "MSpapaa", "pred_fate": "pharynx", "confidence": 0.8452, "true_fate": "pharynx", "correct": true}, {"cell": "MSpapaaa", "pred_fate": "pharynx", "confidence": 0.9579, "true_fate": "pharynx", "correct": true}, {"cell": "MSpapaap", "pred_fate": "pharynx", "confidence": 0.7904, "true_fate": "pharynx", "correct": true}, {"cell": "MSpapap", "pred_fate": "muscle", "confidence": 0.3608, "true_fate": "pharynx", "correct": false}, {"cell": "MSpapapa", "pred_fate": "pharynx", "confidence": 0.6016, "true_fate": "pharynx", "correct": true}, {"cell": "MSpapapp", "pred_fate": "pharynx", "confidence": 0.4408}, {"cell": "MSpapp", "pred_fate": "muscle", "confidence": 0.3449, "true_fate": "muscle", "correct": true}, {"cell": "MSpappa", "pred_fate": "muscle", "confidence": 0.7111, "true_fate": "muscle", "correct": true}, {"cell": "MSpappp", "pred_fate": "muscle", "confidence": 0.779, "true_fate": "muscle", "correct": true}, {"cell": "MSpp", "pred_fate": "muscle", "confidence": 0.5736, "true_fate": "muscle", "correct": true}, {"cell": "MSppa", "pred_fate": "muscle", "confidence": 0.4173}, {"cell": "MSppaa", "pred_fate": "neuron", "confidence": 0.841}, {"cell": "MSppaaa", "pred_fate": "pharynx", "confidence": 0.7311, "true_fate": "pharynx", "correct": true}, {"cell": "MSppaaaa", "pred_fate": "neuron", "confidence": 0.3796, "true_fate": "pharynx", "correct": false}, {"cell": "MSppaaap", "pred_fate": "muscle", "confidence": 0.3312, "true_fate": "muscle", "correct": true}, {"cell": "MSppaap", "pred_fate": "muscle", "confidence": 0.2734, "true_fate": "intestine", "correct": false}, {"cell": "MSppap", "pred_fate": "muscle", "confidence": 0.61, "true_fate": "muscle", "correct": true}, {"cell": "MSppapa", "pred_fate": "muscle", "confidence": 0.5678, "true_fate": "coelomocyte", "correct": false}, {"cell": "MSppapaa", "pred_fate": "muscle", "confidence": 0.54, "true_fate": "coelomocyte", "correct": false}, {"cell": "MSppapap", "pred_fate": "muscle", "confidence": 0.709, "true_fate": "muscle", "correct": true}, {"cell": "MSppapp", "pred_fate": "muscle", "confidence": 0.7048, "true_fate": "muscle", "correct": true}, {"cell": "MSppp", "pred_fate": "muscle", "confidence": 0.7829, "true_fate": "muscle", "correct": true}, {"cell": "MSpppa", "pred_fate": "muscle", "confidence": 0.6546}, {"cell": "MSpppaa", "pred_fate": "muscle", "confidence": 0.3476, "true_fate": "germline", "correct": false}, {"cell": "MSpppap", "pred_fate": "muscle", "confidence": 0.7396, "true_fate": "muscle", "correct": true}, {"cell": "MSpppp", "pred_fate": "muscle", "confidence": 0.7955, "true_fate": "muscle", "correct": true}, {"cell": "MSppppa", "pred_fate": "muscle", "confidence": 0.8175, "true_fate": "muscle", "correct": true}, {"cell": "MSppppp", "pred_fate": "muscle", "confidence": 0.7263, "true_fate": "muscle", "correct": true}, {"cell": "P2", "pred_fate": "muscle", "confidence": 0.3611}, {"cell": "P3", "pred_fate": "muscle", "confidence": 0.5104}, {"cell": "P4", "pred_fate": "germline", "confidence": 0.4875, "true_fate": "germline", "correct": true}, {"cell": "Z2", "pred_fate": "muscle", "confidence": 0.5993, "true_fate": "germline", "correct": false}, {"cell": "Z3", "pred_fate": "muscle", "confidence": 0.563, "true_fate": "germline", "correct": false}]}}}
\ No newline at end of file
diff --git a/Spatio-Temporal-Evolution/dashboard/index.html b/Spatio-Temporal-Evolution/dashboard/index.html
index e4cbf5d..90ba274 100644
--- a/Spatio-Temporal-Evolution/dashboard/index.html
+++ b/Spatio-Temporal-Evolution/dashboard/index.html
@@ -1,106 +1,454 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>ESTGEL 3D Embryo Development & Attention Dashboard</title>
-    <link rel="preconnect" href="https://fonts.googleapis.com">
-    <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
-    <link href="https://fonts.googleapis.com/css2?family=Outfit:wght@300;400;500;700;800&display=swap" rel="stylesheet">
-    <link rel="stylesheet" href="style.css">
-    
-    <!-- Three.js and OrbitControls via CDN -->
-    <script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r128/three.min.js"></script>
-    <script src="https://cdn.jsdelivr.net/npm/three@0.128.0/examples/js/controls/OrbitControls.js"></script>
-    <!-- Chart.js via CDN -->
-    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
-</head>
-<body>
-    <div class="app-container">
-        <!-- Sidebar Controls -->
-        <aside class="sidebar-panel">
-            <header class="app-header">
-                <div class="logo-badge">ESTGEL</div>
-                <h1>Embryo Development Dashboard</h1>
-                <p class="subtitle">Spatio-Temporal GNN & Explainability Explorer</p>
-            </header>
-            
-            <section class="control-section">
-                <h2>Phenotype Selection</h2>
-                <div class="toggle-group">
-                    <button id="btn-wt" class="toggle-btn active">Control (WT)</button>
-                    <button id="btn-rnai" class="toggle-btn">Perturbed (RNAi)</button>
-                </div>
-            </section>
-            
-            <section class="control-section">
-                <h2>Timeline Control</h2>
-                <div class="slider-container">
-                    <input type="range" id="time-slider" min="30" max="180" step="30" value="30">
-                    <div class="slider-labels">
-                        <span>t=30</span>
-                        <span>t=60</span>
-                        <span>t=90</span>
-                        <span>t=120</span>
-                        <span>t=150</span>
-                        <span>t=180</span>
-                    </div>
-                </div>
-                <div class="time-display">Active frame: <span id="current-time-val">30</span></div>
-            </section>
-            
-            <section class="control-section stats-grid">
-                <div class="stat-card">
-                    <span class="stat-label">Active Nodes</span>
-                    <span id="stat-nodes" class="stat-val">0</span>
-                </div>
-                <div class="stat-card">
-                    <span class="stat-label">Active Edges</span>
-                    <span id="stat-edges" class="stat-val">0</span>
-                </div>
-                <div class="stat-card">
-                    <span class="stat-label">Avg EAM Weight</span>
-                    <span id="stat-avg-att" class="stat-val">0.000</span>
-                </div>
-            </section>
-            
-            <section class="control-section">
-                <h2>Top-5 Cell-Cell Interactions</h2>
-                <ul id="interaction-list" class="interaction-list">
-                    <!-- Dynamic Items -->
-                </ul>
-            </section>
-        </aside>
-        
-        <!-- Main Content Area -->
-        <main class="main-content">
-            <!-- 3D Viewport -->
-            <div class="viewport-container">
-                <div class="viewport-header">
-                    <h3>3D Spatial Embryo & Attention Mapping</h3>
-                    <div class="viewport-hint">Drag to Rotate | Scroll to Zoom | Right-click to Pan</div>
-                </div>
-                <div id="three-canvas-container"></div>
-            </div>
-            
-            <!-- Bottom Panel: Curves and Graphs -->
-            <div class="analytics-row">
-                <div class="chart-card">
-                    <h3>Embryo Growth Profile</h3>
-                    <div class="chart-wrapper">
-                        <canvas id="growthChart"></canvas>
-                    </div>
-                </div>
-                <div class="chart-card">
-                    <h3>EAM Attention Contrast (WT vs. RNAi)</h3>
-                    <div class="chart-wrapper">
-                        <canvas id="attentionChart"></canvas>
-                    </div>
-                </div>
-            </div>
-        </main>
+<style>
+  /* ---- ESTGEL cell-fate viewer: committed dark microscopy instrument ---- */
+  :root{
+    --bg:#0a0d13; --panel:#11151d; --panel-2:#151b26; --stage:#05070b;
+    --line:#222a38; --line-soft:#1a212c;
+    --ink:#e8eef7; --muted:#93a0b4; --faint:#5c6879;
+    --accent:#7cc4ff; --accent-dim:#2b4a63;
+    --good:#5ec27a; --warn:#e6b23c; --bad:#e56a6a;
+    --f-neuron:#f4b942; --f-muscle:#ef5a5a; --f-hypodermis:#2fc3b4;
+    --f-pharynx:#b57be8; --f-intestine:#6cc24a; --f-glia:#4d9de0;
+    --f-germline:#e879c0; --f-excretory:#d99a4e; --f-coelomocyte:#9aa7bd;
+    --f-death:#5b6472; --f-other:#7a8699; --f-mixed:#3d4757; --f-unknown:#3d4757;
+    --mono:ui-monospace,"Cascadia Code","SF Mono",Consolas,monospace;
+    --sans:system-ui,"Segoe UI",Roboto,Helvetica,Arial,sans-serif;
+    --r:12px; --r-sm:8px;
+  }
+  *{box-sizing:border-box}
+  body{margin:0;background:
+      radial-gradient(1200px 700px at 78% -10%,#101827 0%,transparent 55%),
+      var(--bg);
+    color:var(--ink);font-family:var(--sans);line-height:1.45;
+    -webkit-font-smoothing:antialiased;}
+  .wrap{max-width:1320px;margin:0 auto;padding:26px 22px 60px;}
+  a{color:var(--accent);text-decoration:none}
+
+  .top{display:flex;justify-content:space-between;align-items:flex-end;gap:24px;
+    flex-wrap:wrap;padding-bottom:18px;border-bottom:1px solid var(--line);}
+  .brand{display:flex;flex-direction:column;gap:7px}
+  .eyebrow{font-family:var(--mono);font-size:11px;letter-spacing:.22em;
+    text-transform:uppercase;color:var(--accent);}
+  h1{font-size:26px;font-weight:650;margin:0;letter-spacing:-.01em;text-wrap:balance}
+  .sub{color:var(--muted);font-size:13.5px;max-width:60ch}
+  .chips{display:flex;gap:10px;flex-wrap:wrap}
+  .chip{background:var(--panel);border:1px solid var(--line);border-radius:var(--r-sm);
+    padding:9px 13px;display:flex;flex-direction:column;gap:2px;min-width:78px}
+  .chip .k{font-family:var(--mono);font-size:10px;letter-spacing:.1em;text-transform:uppercase;color:var(--faint)}
+  .chip .v{font-family:var(--mono);font-size:19px;font-weight:600;font-variant-numeric:tabular-nums}
+
+  .grid{display:grid;grid-template-columns:1fr 312px;gap:16px;margin-top:18px}
+  .card{background:var(--panel);border:1px solid var(--line);border-radius:var(--r);overflow:hidden}
+  .card h2{font-size:12px;letter-spacing:.14em;text-transform:uppercase;color:var(--muted);
+    margin:0;padding:14px 16px;border-bottom:1px solid var(--line-soft);font-weight:600;
+    display:flex;justify-content:space-between;align-items:center;gap:10px}
+  .card h2 .note{font-family:var(--mono);font-size:10px;letter-spacing:.04em;color:var(--faint);text-transform:none}
+
+  .stage-card{display:flex;flex-direction:column}
+  .stage{position:relative;background:
+      radial-gradient(circle at 50% 42%,#0a121d 0%,var(--stage) 70%);
+    aspect-ratio:16/11;min-height:340px}
+  #view{position:absolute;inset:0;width:100%;height:100%;display:block;cursor:grab;touch-action:none}
+  #view:active{cursor:grabbing}
+  .hint{position:absolute;left:14px;bottom:12px;font-family:var(--mono);font-size:10.5px;
+    color:var(--faint);letter-spacing:.03em;pointer-events:none}
+  .frame-tag{position:absolute;right:14px;top:12px;font-family:var(--mono);font-size:11px;
+    color:var(--muted);background:#0009;border:1px solid var(--line);border-radius:6px;padding:4px 9px}
+  .tooltip{position:absolute;pointer-events:none;z-index:5;background:#0c1219ee;border:1px solid var(--line);
+    border-radius:7px;padding:7px 9px;font-family:var(--mono);font-size:11px;opacity:0;transition:opacity .1s;
+    transform:translate(-50%,-118%);white-space:nowrap;box-shadow:0 6px 22px #000a}
+  .tooltip .tn{color:var(--ink);font-weight:600}
+  .tooltip .tf{font-size:10px}
+
+  .transport{display:flex;align-items:center;gap:14px;padding:12px 16px;border-top:1px solid var(--line-soft);flex-wrap:wrap}
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+
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+
+<div class="wrap">
+  <header class="top">
+    <div class="brand">
+      <span class="eyebrow">ESTGEL · DevoGraph</span>
+      <h1>Cell-fate map of a <i>C.&nbsp;elegans</i> embryo</h1>
+      <p class="sub">A spatio-temporal graph network predicts each cell's terminal tissue from its
+        position, size and lineage dynamics — never its name. Play development forward, watch cells
+        divide, and inspect what drives each call.</p>
     </div>
-    
-    <script src="app.js"></script>
-</body>
-</html>
+    <div class="chips" id="chips"></div>
+  </header>
+
+  <div class="grid">
+    <section class="card stage-card">
+      <h2>3D embryo · predicted fate <span class="note" id="emb-name"></span></h2>
+      <div class="stage">
+        <canvas id="view"></canvas>
+        <div class="frame-tag" id="frameTag">t = 0 min</div>
+        <div class="hint">drag to rotate · scroll to zoom · click a cell</div>
+        <div class="tooltip" id="tip"></div>
+      </div>
+      <div class="transport">
+        <button class="play" id="play" aria-label="Play developmental time">▶</button>
+        <div class="scrub">
+          <input type="range" id="slider" min="0" max="29" value="0" step="0.01">
+          <div class="ticks" id="ticks"></div>
+        </div>
+        <div class="toggles">
+          <button class="tg contacts on" id="tgEdges"><span class="sw"></span>contacts</button>
+          <button class="tg miss on" id="tgMiss"><span class="sw"></span>misses</button>
+        </div>
+        <div class="tlabel">t = <b id="tmin">0</b> min</div>
+      </div>
+    </section>
+
+    <aside class="rail">
+      <div class="card">
+        <h2>Tissue fates <span class="note">click to isolate</span></h2>
+        <div class="legend" id="legend"></div>
+      </div>
+      <div class="card">
+        <h2>Cell inspector</h2>
+        <div class="inspect" id="inspect">
+          <div class="insp-empty">Hover or click a cell in the embryo</div>
+        </div>
+      </div>
+    </aside>
+  </div>
+
+  <div class="section-h">
+    <h2>What drives the prediction</h2>
+    <p>Attention weights saturate, so importance is measured by perturbation — remove an input and watch the call move.</p>
+  </div>
+
+  <div class="xgrid">
+    <section class="card">
+      <h2>Do interactions matter? · graph ablation</h2>
+      <div class="panel-b">
+        <div class="headline">
+          <div><div class="big" id="accFull">—</div><div class="lab">accuracy, full graph</div></div>
+          <div class="arrow">→</div>
+          <div><div class="big" id="accNo" style="color:var(--bad)">—</div><div class="lab">edges removed</div></div>
+          <div style="margin-left:auto;text-align:right">
+            <div class="big flip" id="flip">—</div><div class="lab">of fates flip<br>without contacts</div></div>
+        </div>
+        <div class="bars" id="ablBars"></div>
+        <div class="cap">Removing every cell–cell edge and re-predicting. Confidence drop per tissue → contacts carry real fate signal.</div>
+      </div>
+    </section>
+
+    <section class="card">
+      <h2>Which features drive each fate · occlusion</h2>
+      <div class="panel-b">
+        <div id="occHeat"></div>
+        <div class="cap">Confidence lost when a feature is mean-imputed. Warmer = the feature supports that tissue's call.</div>
+      </div>
+    </section>
+
+    <section class="card">
+      <h2>Tissue-to-tissue contacts</h2>
+      <div class="panel-b">
+        <div id="contactHeat"></div>
+        <div class="cap">How often the model sees each tissue in contact with another (log scale). Diagonal = like-fate clustering.</div>
+      </div>
+    </section>
+
+    <section class="card">
+      <h2>Model performance</h2>
+      <div class="panel-b">
+        <div class="metarow">
+          <div>
+            <svg class="spark" id="curve" viewBox="0 0 260 132" preserveAspectRatio="none"></svg>
+            <div class="lgi"><span><i style="background:var(--accent)"></i>val accuracy</span><span><i style="background:var(--f-neuron)"></i>macro-F1</span></div>
+          </div>
+          <div>
+            <div class="bars" id="recallBars"></div>
+          </div>
+        </div>
+      </div>
+    </section>
+  </div>
+
+  <div class="foot">
+    <span id="footL">ESTGEL node classifier · EPIC lineage data</span>
+    <span>fate labels from the invariant C. elegans lineage · trained on held-out embryos</span>
+  </div>
+</div>
+
+<script id="fate-data" type="application/json">{"embryo": "CD011505_end1red_bright.csv", "n_cells": 710, "frames": [0, 8, 15, 23, 30, 38, 45, 53, 60, 68, 76, 83, 91, 98, 106, 113, 121, 128, 136, 143, 151, 159, 166, 174, 181, 189, 196, 204, 211, 219], "fate_classes": ["neuron", "muscle", "hypodermis", "pharynx", "intestine", "glia", "germline", "excretory", "coelomocyte", "death", "other", "mixed", "unknown"], "cells": [{"name": "ABa", "fate": "pharynx", "conf": 0.66, "size": 90.0, "b": 0, "p": -1, "pos": [[238.0, 258.0, 14.9], [189.0, 274.0, 15.7], null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null]}, {"name": "ABal", "fate": "pharynx", "conf": 0.745, "size": 81.0, "b": 2, "p": 0, "pos": [null, null, [177.0, 236.0, 15.1], [143.0, 226.0, 17.3], null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null]}, {"name": "ABala", "fate": "neuron", "conf": 0.508, "size": 69.3, "b": 4, "p": 1, "pos": [null, null, null, null, [136.0, 276.0, 16.1], [121.0, 285.0, 15.0], [135.0, 295.0, 13.1], null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null], "true_fate": "neuron", "correct": true}, {"name": "ABalaa", "fate": "neuron", "conf": 0.585, "size": 61.7, "b": 7, "p": 2, "pos": [null, null, null, null, null, null, null, [100.0, 271.0, 12.9], [99.0, 261.0, 12.8], [106.0, 276.0, 13.7], null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null]}, {"name": "ABalaaa", "fate": "pharynx", "conf": 0.633, "size": 54.4, "b": 10, "p": 3, "pos": [null, null, null, null, null, null, null, null, null, null, [96.0, 282.0, 13.6], [93.0, 287.0, 14.0], [100.0, 297.0, 13.9], [99.0, 296.0, 13.9], [104.0, 289.0, 13.8], null, null, null, null, null, null, null, null, null, null, null, null, null, null, null]}, {"name": "ABalaaaa", "fate": "neuron", "conf": 0.503, "size": 46.2, "b": 15, "p": 4, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [86.0, 256.0, 11.9], [89.0, 279.0, 14.0], [99.0, 298.0, 13.5], [106.0, 308.0, 17.1], [101.0, 300.0, 18.3], null, null, null, null, null, null, null, null, null, null], "true_fate": "neuron", "correct": true}, {"name": "ABalaaaal", "fate": "pharynx", "conf": 0.822, "size": 38.0, "b": 20, "p": 5, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [98.0, 258.0, 17.1], [95.0, 245.0, 15.4], [101.0, 234.0, 15.2], [103.0, 229.0, 14.4], [108.0, 216.0, 13.1], [100.0, 219.0, 13.8], [103.0, 223.0, 12.4], null, null, null]}, {"name": "ABalaaaala", "fate": "pharynx", "conf": 0.503, "size": 30.7, "b": 27, "p": 6, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [101.0, 212.0, 13.3], [102.0, 208.0, 13.2], [103.0, 218.0, 12.6]], "true_fate": "neuron", "correct": false}, {"name": "ABalaaaalp", "fate": "pharynx", "conf": 0.725, "size": 34.3, "b": 27, "p": 6, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [126.0, 188.0, 11.1], [138.0, 189.0, 12.8], [128.0, 192.0, 11.0]], "true_fate": "glia", "correct": false}, {"name": "ABalaaaar", "fate": "pharynx", "conf": 0.384, "size": 36.9, "b": 20, "p": 5, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [96.0, 288.0, 13.2], [92.0, 299.0, 12.2], [82.0, 282.0, 13.0], [78.0, 274.0, 13.1], [80.0, 277.0, 12.9], [80.0, 275.0, 14.1], [83.0, 283.0, 13.0], null, null, null], "true_fate": "neuron", "correct": false}, {"name": "ABalaaaarl", "fate": "pharynx", "conf": 0.59, "size": 36.3, "b": 27, "p": 9, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [93.0, 245.0, 11.3], [90.0, 248.0, 11.3], [87.0, 260.0, 12.3]], "true_fate": "neuron", "correct": false}, {"name": "ABalaaaarr", "fate": "neuron", "conf": 0.455, "size": 34.3, "b": 27, "p": 9, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [88.0, 286.0, 13.1], [99.0, 302.0, 12.0], [97.0, 307.0, 13.0]], "true_fate": "neuron", "correct": true}, {"name": "ABalaaap", "fate": "neuron", "conf": 0.56, "size": 46.6, "b": 15, "p": 4, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [138.0, 303.0, 14.9], [125.0, 317.0, 15.9], [134.0, 307.0, 16.5], [152.0, 326.0, 17.5], [153.0, 310.0, 16.1], null, null, null, null, null, null, null, null, null, null], "true_fate": "glia", "correct": false}, {"name": "ABalaaapa", "fate": "neuron", "conf": 0.471, "size": 39.8, "b": 20, "p": 12, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [123.0, 297.0, 16.2], [97.0, 290.0, 16.1], [92.0, 271.0, 17.2], [90.0, 264.0, 17.2], [92.0, 261.0, 16.4], [90.0, 266.0, 17.1], null, null, null, null], "true_fate": "glia", "correct": false}, {"name": "ABalaaapal", "fate": "pharynx", "conf": 0.489, "size": 36.5, "b": 26, "p": 13, "pos": [null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, [84.0, 243.0, 17.1], [95.0, 217.0, 16.0], [104.0, 232.0, 15.3], [102.0, 226.0, 15.1]]}, {"name": "ABalaaapar", "fate": "glia", "conf": 0.385, "size": 32.5, "b": 26, "p": 13, "pos": [null, null, null, null, null, null, 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"confidence": 0.581, "true_fate": "pharynx", "correct": true}, {"cell": "MSapaaap", "pred_fate": "pharynx", "confidence": 0.5202, "true_fate": "muscle", "correct": false}, {"cell": "MSapaap", "pred_fate": "pharynx", "confidence": 0.436, "true_fate": "other", "correct": false}, {"cell": "MSapap", "pred_fate": "muscle", "confidence": 0.5164, "true_fate": "muscle", "correct": true}, {"cell": "MSapapa", "pred_fate": "pharynx", "confidence": 0.3059, "true_fate": "coelomocyte", "correct": false}, {"cell": "MSapapaa", "pred_fate": "muscle", "confidence": 0.338, "true_fate": "coelomocyte", "correct": false}, {"cell": "MSapapap", "pred_fate": "muscle", "confidence": 0.4172, "true_fate": "muscle", "correct": true}, {"cell": "MSapapp", "pred_fate": "muscle", "confidence": 0.4904, "true_fate": "muscle", "correct": true}, {"cell": "MSapappa", "pred_fate": "muscle", "confidence": 0.4498, "true_fate": "muscle", "correct": true}, {"cell": "MSapappp", "pred_fate": "muscle", "confidence": 0.3755, "true_fate": "muscle", "correct": true}, {"cell": "MSapp", "pred_fate": "muscle", "confidence": 0.6677, "true_fate": "muscle", "correct": true}, {"cell": "MSappa", "pred_fate": "pharynx", "confidence": 0.4526}, {"cell": "MSappaa", "pred_fate": "muscle", "confidence": 0.3498}, {"cell": "MSappap", "pred_fate": "muscle", "confidence": 0.7139, "true_fate": "muscle", "correct": true}, {"cell": "MSappp", "pred_fate": "muscle", "confidence": 0.6429, "true_fate": "muscle", "correct": true}, {"cell": "MSapppa", "pred_fate": "muscle", "confidence": 0.5132, "true_fate": "muscle", "correct": true}, {"cell": "MSapppp", "pred_fate": "muscle", "confidence": 0.6025, "true_fate": "muscle", "correct": true}, {"cell": "MSp", "pred_fate": "muscle", "confidence": 0.4002}, {"cell": "MSpa", "pred_fate": "pharynx", "confidence": 0.4959, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaa", "pred_fate": "pharynx", "confidence": 0.7684, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaa", "pred_fate": "pharynx", "confidence": 0.7754, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaaa", "pred_fate": "neuron", "confidence": 0.3906, "true_fate": "pharynx", "correct": false}, {"cell": "MSpaaaaa", "pred_fate": "pharynx", "confidence": 0.853, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaaap", "pred_fate": "pharynx", "confidence": 0.9505, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaap", "pred_fate": "pharynx", "confidence": 0.8948, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaapa", "pred_fate": "pharynx", "confidence": 0.7573, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaaapp", "pred_fate": "pharynx", "confidence": 0.6295, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaap", "pred_fate": "pharynx", "confidence": 0.8167, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaapa", "pred_fate": "pharynx", "confidence": 0.8085, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaapaa", "pred_fate": "pharynx", "confidence": 0.9076, "true_fate": "pharynx", "correct": true}, {"cell": "MSpaapap", "pred_fate": "pharynx", "confidence": 0.4335}, {"cell": "MSpaapp", "pred_fate": "neuron", "confidence": 0.3601, "true_fate": "pharynx", "correct": false}, {"cell": "MSpap", "pred_fate": "pharynx", "confidence": 0.6564}, {"cell": "MSpapa", "pred_fate": "pharynx", "confidence": 0.8497, "true_fate": "pharynx", "correct": true}, {"cell": "MSpapaa", "pred_fate": "pharynx", "confidence": 0.8452, "true_fate": "pharynx", "correct": true}, {"cell": "MSpapaaa", "pred_fate": "pharynx", "confidence": 0.9579, "true_fate": "pharynx", "correct": true}, {"cell": "MSpapaap", "pred_fate": "pharynx", "confidence": 0.7904, "true_fate": "pharynx", "correct": true}, {"cell": "MSpapap", "pred_fate": "muscle", "confidence": 0.3608, "true_fate": "pharynx", "correct": false}, {"cell": "MSpapapa", "pred_fate": "pharynx", "confidence": 0.6016, "true_fate": "pharynx", "correct": true}, {"cell": "MSpapapp", "pred_fate": "pharynx", "confidence": 0.4408}, {"cell": "MSpapp", "pred_fate": "muscle", "confidence": 0.3449, "true_fate": "muscle", "correct": true}, {"cell": "MSpappa", "pred_fate": "muscle", "confidence": 0.7111, "true_fate": "muscle", "correct": true}, {"cell": "MSpappp", "pred_fate": "muscle", "confidence": 0.779, "true_fate": "muscle", "correct": true}, {"cell": "MSpp", "pred_fate": "muscle", "confidence": 0.5736, "true_fate": "muscle", "correct": true}, {"cell": "MSppa", "pred_fate": "muscle", "confidence": 0.4173}, {"cell": "MSppaa", "pred_fate": "neuron", "confidence": 0.841}, {"cell": "MSppaaa", "pred_fate": "pharynx", "confidence": 0.7311, "true_fate": "pharynx", "correct": true}, {"cell": "MSppaaaa", "pred_fate": "neuron", "confidence": 0.3796, "true_fate": "pharynx", "correct": false}, {"cell": "MSppaaap", "pred_fate": "muscle", "confidence": 0.3312, "true_fate": "muscle", "correct": true}, {"cell": "MSppaap", "pred_fate": "muscle", "confidence": 0.2734, "true_fate": "intestine", "correct": false}, {"cell": "MSppap", "pred_fate": "muscle", "confidence": 0.61, "true_fate": "muscle", "correct": true}, {"cell": "MSppapa", "pred_fate": "muscle", "confidence": 0.5678, "true_fate": "coelomocyte", "correct": false}, {"cell": "MSppapaa", "pred_fate": "muscle", "confidence": 0.54, "true_fate": "coelomocyte", "correct": false}, {"cell": "MSppapap", "pred_fate": "muscle", "confidence": 0.709, "true_fate": "muscle", "correct": true}, {"cell": "MSppapp", "pred_fate": "muscle", "confidence": 0.7048, "true_fate": "muscle", "correct": true}, {"cell": "MSppp", "pred_fate": "muscle", "confidence": 0.7829, "true_fate": "muscle", "correct": true}, {"cell": "MSpppa", "pred_fate": "muscle", "confidence": 0.6546}, {"cell": "MSpppaa", "pred_fate": "muscle", "confidence": 0.3476, "true_fate": "germline", "correct": false}, {"cell": "MSpppap", "pred_fate": "muscle", "confidence": 0.7396, "true_fate": "muscle", "correct": true}, {"cell": "MSpppp", "pred_fate": "muscle", "confidence": 0.7955, "true_fate": "muscle", "correct": true}, {"cell": "MSppppa", "pred_fate": "muscle", "confidence": 0.8175, "true_fate": "muscle", "correct": true}, {"cell": "MSppppp", "pred_fate": "muscle", "confidence": 0.7263, "true_fate": "muscle", "correct": true}, {"cell": "P2", "pred_fate": "muscle", "confidence": 0.3611}, {"cell": "P3", "pred_fate": "muscle", "confidence": 0.5104}, {"cell": "P4", "pred_fate": "germline", "confidence": 0.4875, "true_fate": "germline", "correct": true}, {"cell": "Z2", "pred_fate": "muscle", "confidence": 0.5993, "true_fate": "germline", "correct": false}, {"cell": "Z3", "pred_fate": "muscle", "confidence": 0.563, "true_fate": "germline", "correct": false}]}}}</script>
+<script>
+(function(){
+  const DATA = JSON.parse(document.getElementById('fate-data').textContent);
+  const css = getComputedStyle(document.documentElement);
+  const colorCache={};
+  const colorOf = f => colorCache[f] || (colorCache[f]=(css.getPropertyValue('--f-'+f).trim()||'#7a8699'));
+
+  /* ---------- header chips ---------- */
+  const hist=(DATA.metrics.history||[]), last=hist[hist.length-1]||{};
+  const chips=[['cells',DATA.n_cells],['val acc',last.val_acc!=null?(last.val_acc*100).toFixed(0)+'%':'—'],
+    ['macro-F1',last.val_macro_f1!=null?last.val_macro_f1.toFixed(2):'—'],
+    ['tissues',new Set(DATA.cells.map(c=>c.fate)).size]];
+  document.getElementById('chips').innerHTML=chips.map(([k,v])=>`<div class="chip"><span class="k">${k}</span><span class="v">${v}</span></div>`).join('');
+  document.getElementById('emb-name').textContent=DATA.embryo;
+  document.getElementById('footL').textContent='ESTGEL node classifier · '+DATA.embryo;
+
+  /* ---------- legend ---------- */
+  const counts={}; DATA.cells.forEach(c=>counts[c.fate]=(counts[c.fate]||0)+1);
+  const fates=Object.keys(counts).sort((a,b)=>counts[b]-counts[a]);
+  const maxCt=Math.max(...Object.values(counts)), hidden=new Set();
+  const legend=document.getElementById('legend');
+  legend.innerHTML=fates.map(f=>`
+    <div class="lg" data-f="${f}" style="color:${colorOf(f)}">
+      <span class="dot" style="background:${colorOf(f)}"></span>
+      <span style="flex:1"><span style="display:flex;justify-content:space-between">
+        <span class="nm" style="color:var(--ink)">${f}</span><span class="ct">${counts[f]}</span></span>
+        <span class="bar" style="width:${Math.max(8,counts[f]/maxCt*100)}%;display:block"></span></span></div>`).join('');
+  legend.querySelectorAll('.lg').forEach(el=>el.onclick=()=>{
+    const f=el.dataset.f; hidden.has(f)?(hidden.delete(f),el.classList.remove('off')):(hidden.add(f),el.classList.add('off'));});
+
+  /* ---------- 3D engine ---------- */
+  const cv=document.getElementById('view'), ctx=cv.getContext('2d');
+  const cells=DATA.cells, frames=DATA.frames, edges=DATA.edges||[], NF=frames.length;
+  let yaw=0.6, pitch=-0.35, zoom=1, dragging=false, autoRot=true, sel=-1, hover=-1;
+  let lx=0,ly=0, dpr=Math.min(window.devicePixelRatio||1,2);
+  let t=0, playing=false, speed=0.5;
+  let showEdges=true, showMiss=true;
+
+  let cx=0,cy=0,cz=0,nc=0;
+  cells.forEach(c=>{const p=c.pos[NF-1]||c.pos.find(Boolean);if(p){cx+=p[0];cy+=p[1];cz+=p[2];nc++;}});
+  cx/=nc;cy/=nc;cz/=nc;
+  let sp=0,n2=0; cells.forEach(c=>c.pos.forEach(p=>{if(p){sp+=(p[0]-cx)**2+(p[1]-cy)**2+(p[2]-cz)**2;n2++;}}));
+  const spread=Math.sqrt(sp/n2)||1;
+
+  function resize(){const r=cv.getBoundingClientRect();cv.width=r.width*dpr;cv.height=r.height*dpr;}
+  window.addEventListener('resize',resize);
+
+  function sample(c,tt){
+    const f0=Math.floor(tt), f1=Math.min(f0+1,NF-1), a=tt-f0;
+    const p0=c.pos[f0], p1=c.pos[f1];
+    if(p0&&p1){return {p:[p0[0]+(p1[0]-p0[0])*a,p0[1]+(p1[1]-p0[1])*a,p0[2]+(p1[2]-p0[2])*a],grow:1,alpha:1};}
+    if(!p0&&p1){ let src=p1; if(c.p>=0){const par=cells[c.p].pos[f0]; if(par)src=par;}
+      return {p:[src[0]+(p1[0]-src[0])*a,src[1]+(p1[1]-src[1])*a,src[2]+(p1[2]-src[2])*a],grow:0.25+0.75*a,alpha:0.15+0.85*a,from:src};}
+    if(p0&&!p1){return {p:p0,grow:1-a*0.5,alpha:1-a};}
+    return null;
+  }
+  let rot={};
+  function setRot(){rot={cyw:Math.cos(yaw),syw:Math.sin(yaw),cp:Math.cos(pitch),sp2:Math.sin(pitch)};}
+  function project(P,W,H,R){const {cyw,syw,cp,sp2}=rot; let X=P[0]-cx,Y=P[1]-cy,Z=P[2]-cz;
+    let x1=X*cyw+Z*syw, z1=-X*syw+Z*cyw, y1=Y*cp-z1*sp2, z2=Y*sp2+z1*cp;
+    return {sx:W/2+x1*R, sy:H/2+y1*R, depth:z2};}
+
+  let lastPts=[];
+  function draw(){
+    const W=cv.width,H=cv.height; ctx.clearRect(0,0,W,H); setRot();
+    const R=Math.min(W,H)*0.34*zoom/spread;
+    const f0=Math.min(Math.floor(t),NF-1);
+    const S=new Array(cells.length); const pts=[];
+    for(let i=0;i<cells.length;i++){
+      const c=cells[i]; if(hidden.has(c.fate)){S[i]=null;continue;}
+      const s=sample(c,t); S[i]=s; if(!s)continue;
+      const pr=project(s.p,W,H,R);
+      pts.push({i,sx:pr.sx,sy:pr.sy,depth:pr.depth,s,fate:c.fate,conf:c.conf,sz:c.size,miss:c.correct===false});
+    }
+    const zs=pts.map(p=>p.depth), zmn=zs.length?Math.min(...zs):0, zmx=zs.length?Math.max(...zs):1, zr=(zmx-zmn)||1;
+    if(showEdges && edges[f0]){
+      ctx.lineWidth=Math.max(0.5,0.7*dpr);
+      for(const e of edges[f0]){
+        const si=S[e[0]], sj=S[e[1]]; if(!si||!sj)continue;
+        const a=project(si.p,W,H,R), b=project(sj.p,W,H,R);
+        const tt=((a.depth+b.depth)/2-zmn)/zr;
+        ctx.strokeStyle=`rgba(124,196,255,${0.05+0.14*tt})`;
+        ctx.beginPath();ctx.moveTo(a.sx,a.sy);ctx.lineTo(b.sx,b.sy);ctx.stroke();
+      }
+    }
+    pts.sort((p,q)=>p.depth-q.depth);
+    for(const p of pts){
+      const d=(p.depth-zmn)/zr;
+      const rad=(2.2+(p.sz/45)*3.0)*dpr*(0.6+0.5*d)*zoom*p.s.grow;
+      const col=colorOf(p.fate);
+      if(p.s.from){const fp=project(p.s.from,W,H,R);
+        ctx.strokeStyle=col+'66';ctx.lineWidth=1.1*dpr;
+        ctx.beginPath();ctx.moveTo(fp.sx,fp.sy);ctx.lineTo(p.sx,p.sy);ctx.stroke();}
+      const conf=0.45+0.55*p.conf;
+      ctx.globalAlpha=(0.3+0.6*d)*p.s.alpha*conf;
+      ctx.beginPath();ctx.arc(p.sx,p.sy,rad*2.1,0,7);ctx.fillStyle=col+'22';ctx.fill();
+      ctx.globalAlpha=(0.5+0.5*d)*p.s.alpha*conf;
+      ctx.beginPath();ctx.arc(p.sx,p.sy,rad,0,7);ctx.fillStyle=col;ctx.fill();
+      if(showMiss && p.miss){ctx.globalAlpha=0.9*p.s.alpha;ctx.strokeStyle='#e56a6a';ctx.lineWidth=1.4*dpr;
+        ctx.beginPath();ctx.arc(p.sx,p.sy,rad+3.5*dpr,0,7);ctx.stroke();}
+      if(p.i===sel||p.i===hover){ctx.globalAlpha=1;ctx.lineWidth=1.6*dpr;
+        ctx.strokeStyle=p.i===sel?'#fff':'#ffffffaa';
+        ctx.beginPath();ctx.arc(p.sx,p.sy,rad+3*dpr,0,7);ctx.stroke();}
+    }
+    ctx.globalAlpha=1; lastPts=pts;
+    const tmin=Math.round(frames[f0]+(frames[Math.min(f0+1,NF-1)]-frames[f0])*(t-f0));
+    document.getElementById('frameTag').textContent='t = '+tmin+' min';
+    document.getElementById('tmin').textContent=tmin;
+  }
+
+  function pick(mx,my){let best=-1,bd=13*dpr;
+    for(const p of lastPts){const d=Math.hypot(p.sx-mx*dpr,p.sy-my*dpr);if(d<bd){bd=d;best=p.i;}}return best;}
+
+  cv.addEventListener('pointerdown',e=>{dragging=true;autoRot=false;lx=e.clientX;ly=e.clientY;cv.setPointerCapture(e.pointerId);});
+  cv.addEventListener('pointerup',e=>{
+    if(Math.abs(e.clientX-lx)<3&&Math.abs(e.clientY-ly)<3){const r=cv.getBoundingClientRect();sel=pick(e.clientX-r.left,e.clientY-r.top);inspect(sel);}
+    dragging=false;});
+  cv.addEventListener('pointermove',e=>{const r=cv.getBoundingClientRect();
+    if(dragging){yaw+=(e.clientX-lx)*0.01;pitch=Math.max(-1.4,Math.min(1.4,pitch+(e.clientY-ly)*0.01));lx=e.clientX;ly=e.clientY;}
+    else{const h=pick(e.clientX-r.left,e.clientY-r.top);hover=h;const tip=document.getElementById('tip');
+      if(h>=0){const c=cells[h];tip.style.opacity=1;tip.style.left=(e.clientX-r.left)+'px';tip.style.top=(e.clientY-r.top)+'px';
+        tip.innerHTML=`<div class="tn">${c.name}</div><div class="tf" style="color:${colorOf(c.fate)}">${c.fate} · ${(c.conf*100).toFixed(0)}%${c.correct===false?' · miss':''}</div>`;}
+      else tip.style.opacity=0;}});
+  cv.addEventListener('pointerleave',()=>{hover=-1;document.getElementById('tip').style.opacity=0;});
+  cv.addEventListener('wheel',e=>{e.preventDefault();zoom=Math.max(0.4,Math.min(3.2,zoom*(e.deltaY<0?1.1:0.9)));},{passive:false});
+
+  function inspect(i){const box=document.getElementById('inspect');
+    if(i<0){box.innerHTML='<div class="insp-empty">Hover or click a cell in the embryo</div>';return;}
+    const c=cells[i];
+    const truth=c.true_fate!=null
+      ?`<div class="insp-row"><span class="k">true fate</span><span class="v"><span class="tag" style="background:${colorOf(c.true_fate)}22;color:${colorOf(c.true_fate)}"><span class="dot" style="background:${colorOf(c.true_fate)}"></span>${c.true_fate}</span></span></div>
+        <div class="insp-row"><span class="k">verdict</span><span class="verdict ${c.correct?'ok':'no'}">${c.correct?'correct':'miss'}</span></div>`
+      :`<div class="insp-row"><span class="k">true fate</span><span class="v" style="color:var(--faint)">progenitor / mixed</span></div>`;
+    const par=c.p>=0?cells[c.p].name:'—';
+    box.innerHTML=`<div class="insp-name" style="color:${colorOf(c.fate)}">${c.name}</div>
+      <div class="insp-row"><span class="k">predicted</span><span class="v"><span class="tag" style="background:${colorOf(c.fate)}22;color:${colorOf(c.fate)}"><span class="dot" style="background:${colorOf(c.fate)}"></span>${c.fate}</span></span></div>
+      <div class="insp-row"><span class="k">confidence</span><span class="v">${(c.conf*100).toFixed(1)}%</span></div>
+      <div class="meter"><i style="width:${c.conf*100}%;background:${colorOf(c.fate)}"></i></div>
+      ${truth}
+      <div class="insp-row"><span class="k">parent</span><span class="v">${par}</span></div>
+      <div class="insp-row" style="border:none"><span class="k">born · size</span><span class="v">t${frames[c.b]} · ${c.size}</span></div>`;}
+
+  /* transport */
+  const slider=document.getElementById('slider');
+  slider.max=NF-1;
+  document.getElementById('ticks').innerHTML=frames.map((tt,i)=>(i%6===0||i===NF-1)?`<span>${tt}</span>`:'<span></span>').join('');
+  slider.oninput=()=>{t=+slider.value;};
+  const playBtn=document.getElementById('play');
+  playBtn.onclick=()=>{playing=!playing;playBtn.textContent=playing?'❚❚':'▶';};
+  const tgE=document.getElementById('tgEdges'), tgM=document.getElementById('tgMiss');
+  tgE.onclick=()=>{showEdges=!showEdges;tgE.classList.toggle('on',showEdges);};
+  tgM.onclick=()=>{showMiss=!showMiss;tgM.classList.toggle('on',showMiss);};
+
+  if(matchMedia('(prefers-reduced-motion:reduce)').matches){autoRot=false;}
+  let prev=0;
+  function loop(ts){
+    const dt=Math.min((ts-prev)/1000||0,0.05); prev=ts;
+    if(playing){t+=speed*dt; if(t>=NF-1){t=0;} slider.value=t;}
+    if(autoRot && !dragging){yaw+=0.12*dt;}
+    draw(); requestAnimationFrame(loop);
+  }
+
+  /* ---------- explainability panels ---------- */
+  const sal=DATA.explainability.saliency, inter=DATA.explainability.interactions;
+  const MAJ=['neuron','muscle','hypodermis','pharynx','intestine'];
+  if(sal){
+    document.getElementById('accFull').textContent=(sal.accuracy_full*100).toFixed(0)+'%';
+    document.getElementById('accNo').textContent=(sal.accuracy_no_edges*100).toFixed(0)+'%';
+    document.getElementById('flip').textContent=(sal.prediction_flip_rate_no_edges*100).toFixed(0)+'%';
+    const abl=sal.graph_ablation_confdrop_by_fate||{}, rows=MAJ.filter(f=>f in abl);
+    const amax=Math.max(...rows.map(f=>Math.abs(abl[f])))||1;
+    document.getElementById('ablBars').innerHTML=rows.map(f=>{const v=abl[f],w=Math.abs(v)/amax*100,neg=v<0;
+      return `<div class="brow"><span class="bl">${f}</span><span class="track"><i style="width:${w}%;background:${neg?'var(--faint)':colorOf(f)}"></i></span><span class="bv">${v>=0?'+':''}${v.toFixed(2)}</span></div>`;}).join('');
+    const occ=sal.feature_occlusion_confdrop_by_fate||{}, feats=sal.features||['x','y','z','size','blot'];
+    let allv=[]; MAJ.forEach(f=>occ[f]&&occ[f].forEach(v=>allv.push(Math.abs(v))));
+    const omax=Math.max(...allv,0.001);
+    const hcol=v=>{const q=Math.max(-1,Math.min(1,v/omax));return q>=0?`rgba(244,185,66,${0.12+0.8*q})`:`rgba(90,110,140,${0.12+0.8*-q})`;};
+    let html='<table class="heat"><tr><th></th>'+feats.map(f=>`<th>${f}</th>`).join('')+'</tr>';
+    MAJ.filter(f=>occ[f]).forEach(f=>{html+=`<tr><td class="rl">${f}</td>`+occ[f].map(v=>`<td class="c" style="background:${hcol(v)}">${v.toFixed(2)}</td>`).join('')+'</tr>';});
+    document.getElementById('occHeat').innerHTML=html+'</table>';
+  }
+  if(inter&&inter.contact_counts){
+    const cc=inter.contact_counts, present=inter.tissue_pairs_present.filter(f=>MAJ.includes(f));
+    let mx=0; present.forEach(a=>present.forEach(b=>{const v=(cc[a]||{})[b]||0;if(v>mx)mx=v;}));
+    const lm=Math.log1p(mx)||1, cscale=v=>`rgba(124,196,255,${0.06+0.9*Math.log1p(v)/lm})`;
+    let html='<table class="heat"><tr><th></th>'+present.map(f=>`<th>${f.slice(0,4)}</th>`).join('')+'</tr>';
+    present.forEach(a=>{html+=`<tr><td class="rl">${a}</td>`+present.map(b=>{const v=(cc[a]||{})[b]||0;return `<td class="c" style="background:${cscale(v)}">${v||''}</td>`;}).join('')+'</tr>';});
+    document.getElementById('contactHeat').innerHTML=html+'</table>';
+  }
+  if(hist.length){
+    const W=260,H=132,pad=6,n=hist.length, xs=i=>pad+(n>1?i/(n-1):0.5)*(W-2*pad), yA=v=>H-pad-v*(H-2*pad);
+    const line=(key,col)=>{const d=hist.map((h,i)=>`${i?'L':'M'}${xs(i).toFixed(1)},${yA(h[key]).toFixed(1)}`).join(' ');
+      return `<path d="${d}" fill="none" stroke="${col}" stroke-width="2" stroke-linejoin="round"/><circle cx="${xs(n-1)}" cy="${yA(hist[n-1][key])}" r="3" fill="${col}"/>`;};
+    let grid=''; for(let g=0;g<=1;g+=0.25)grid+=`<line x1="${pad}" y1="${yA(g)}" x2="${W-pad}" y2="${yA(g)}" stroke="#ffffff10"/>`;
+    document.getElementById('curve').innerHTML=grid+line('val_acc',css.getPropertyValue('--accent'))+line('val_macro_f1',css.getPropertyValue('--f-neuron'));
+  }
+  const rec=DATA.metrics.per_class_recall||{}, rkeys=Object.keys(rec).sort((a,b)=>rec[b]-rec[a]);
+  document.getElementById('recallBars').innerHTML='<div style="font-size:11px;color:var(--muted);margin-bottom:8px;text-transform:uppercase;letter-spacing:.1em">Per-class recall</div>'+
+    rkeys.map(f=>`<div class="brow"><span class="bl">${f}</span><span class="track"><i style="width:${rec[f]*100}%;background:${colorOf(f)}"></i></span><span class="bv">${(rec[f]*100).toFixed(0)}%</span></div>`).join('');
+
+  resize(); draw(); requestAnimationFrame(loop);
+})();
+</script>
diff --git a/Spatio-Temporal-Evolution/dashboard/style.css b/Spatio-Temporal-Evolution/dashboard/style.css
deleted file mode 100644
index 1def46e..0000000
--- a/Spatio-Temporal-Evolution/dashboard/style.css
+++ /dev/null
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-/* =========================================================================
-   ESTGEL Dashboard Styling - Modern Dark Mode & Glassmorphism
-   ========================================================================= */
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diff --git a/Spatio-Temporal-Evolution/labels.csv b/Spatio-Temporal-Evolution/labels.csv
new file mode 100644
index 0000000..01fd24b
--- /dev/null
+++ b/Spatio-Temporal-Evolution/labels.csv
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diff --git a/Spatio-Temporal-Evolution/requirements.txt b/Spatio-Temporal-Evolution/requirements.txt
index e512574..487b9c7 100644
--- a/Spatio-Temporal-Evolution/requirements.txt
+++ b/Spatio-Temporal-Evolution/requirements.txt
@@ -3,3 +3,5 @@ pandas
 scipy
 tqdm
 matplotlib
+torch
+torch_geometric
diff --git a/Spatio-Temporal-Evolution/scripts/build_cell_fate.py b/Spatio-Temporal-Evolution/scripts/build_cell_fate.py
new file mode 100644
index 0000000..7db5db0
--- /dev/null
+++ b/Spatio-Temporal-Evolution/scripts/build_cell_fate.py
@@ -0,0 +1,83 @@
+"""
+Generate the node-level cell-fate label map for all cells observed across the
+processed EPIC embryos, using src/cell_fate.CellFateMap.
+
+Outputs:
+  Dataset/fate/cell_fate.csv   columns: cell,fate,fate_id,method,purity,n_leaves,n_embryos
+and prints a coverage + class-distribution report.
+"""
+from __future__ import annotations
+
+import argparse
+import glob
+import sys
+from collections import Counter
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(REPO_ROOT))
+
+from src.cell_fate import CellFateMap, build_fate_index
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--processed-dir", type=Path,
+                    default=REPO_ROOT / "Dataset" / "processed" / "by_embryo")
+    ap.add_argument("--out", type=Path, default=REPO_ROOT / "Dataset" / "fate" / "cell_fate.csv")
+    args = ap.parse_args()
+
+    fate_map = CellFateMap.from_reference()
+    fate_index = build_fate_index()
+
+    npzs = sorted(glob.glob(str(args.processed_dir / "*.npz")))
+    if not npzs:
+        raise SystemExit(f"No .npz embryos in {args.processed_dir}")
+
+    cell_embryos: Counter[str] = Counter()
+    for fp in npzs:
+        z = np.load(fp, allow_pickle=True)
+        for c in {str(c) for c in z["idx_to_cell"]}:
+            cell_embryos[c] += 1
+
+    rows = []
+    for cell in sorted(cell_embryos):
+        r = fate_map.resolve(cell)
+        rows.append({
+            "cell": cell,
+            "fate": r.fate,
+            "fate_id": fate_index[r.fate],
+            "method": r.method,
+            "purity": round(r.purity, 3),
+            "n_leaves": r.n_leaves,
+            "n_embryos": cell_embryos[cell],
+        })
+
+    df = pd.DataFrame(rows)
+    args.out.parent.mkdir(parents=True, exist_ok=True)
+    df.to_csv(args.out, index=False)
+
+    total = len(df)
+    print("=" * 68)
+    print(f"Cell-fate map: {total} unique cells across {len(npzs)} embryos -> {args.out}")
+    print("=" * 68)
+    print("\nFate distribution (unique cells):")
+    for fate, n in df["fate"].value_counts().items():
+        print(f"  {fate:12} {n:5}  ({n/total:5.1%})")
+    print("\nResolution method:")
+    for m, n in df["method"].value_counts().items():
+        print(f"  {m:10} {n:5}  ({n/total:5.1%})")
+    unknown = df[df["fate"] == "unknown"]["cell"].tolist()
+    print(f"\nUnknown ({len(unknown)}): {unknown[:25]}")
+    # Weighted by how often a cell actually appears in embryos:
+    appear = (df["fate"].repeat(df["n_embryos"])).value_counts(normalize=True)
+    print("\nFate distribution (weighted by embryo occurrences):")
+    for fate, frac in appear.items():
+        print(f"  {fate:12} {frac:5.1%}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/Spatio-Temporal-Evolution/scripts/export_dashboard_data.py b/Spatio-Temporal-Evolution/scripts/export_dashboard_data.py
new file mode 100644
index 0000000..0191e6b
--- /dev/null
+++ b/Spatio-Temporal-Evolution/scripts/export_dashboard_data.py
@@ -0,0 +1,151 @@
+"""
+Export a single self-contained data blob for the fate dashboard.
+
+Runs the trained ESTGEL fate model on one embryo and packages:
+  - per-cell predicted fate + confidence + true fate + 3D positions over time
+  - developmental frames (timesteps)
+  - global explainability (feature occlusion, graph ablation, tissue interaction map)
+  - training history + per-class recall
+
+Writes dashboard/fate_dashboard_data.json
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+import numpy as np
+import torch
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(REPO_ROOT))
+
+from src.cell_fate import FATE_CLASSES, build_fate_index, fate_targets, load_fate_csv
+from src.epic_dataset import EpicEmbryoDataset
+from src.epic_preprocess import lineage_parent
+from src.estgel_node import ESTGELNodeClassifier
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--embryo", type=str, default="CD011505_end1red_bright.npz")
+    ap.add_argument("--n-frames", type=int, default=30)
+    ap.add_argument("--max-edges", type=int, default=650, help="cap contact edges drawn per frame")
+    args = ap.parse_args()
+
+    ckpt = REPO_ROOT / "checkpoints" / "estgel_fate"
+    cfg = json.loads((ckpt / "config.json").read_text())
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    fi = build_fate_index(); inv = {v: k for k, v in fi.items()}
+    cell_fate = load_fate_csv()
+
+    ds = EpicEmbryoDataset(cfg["processed_dir"], use_global_index=False)
+    idx = ds.filenames.index(args.embryo) if args.embryo in ds.filenames else 0
+    data = ds[idx]
+    names = [str(c) for c in data.idx_to_cell]
+    labels, valid = fate_targets(data.idx_to_cell, cell_fate, fi)
+
+    # Raw (un-normalized) features straight from the npz — model() mutates data.x in place.
+    raw = np.load(ds.processed_dir / ds.filenames[idx], allow_pickle=True)
+    X = raw["X"]                  # (N, d, T)  raw x,y,z,size,blot
+    am = raw["alive_mask"]        # (N, T)
+
+    drl = {"Lz": cfg["drl_channels"], "Lr": cfg["drl_channels"], "Lh": cfg["drl_channels"]} if cfg.get("drl_channels") else {}
+    model = ESTGELNodeClassifier(
+        num_classes=len(FATE_CLASSES), K=cfg["K"], in_dim=5,
+        recurrence_stride=cfg["recurrence_stride"], max_steps=cfg["max_steps"],
+        bptt_truncation=cfg["bptt_truncation"], max_nodes=cfg["max_nodes"], **drl,
+    ).to(device)
+    model.load_state_dict(torch.load(ckpt / "best.pt", map_location=device)["model_state_dict"])
+    model.eval()
+    with torch.no_grad():
+        logits, _, _ = model(data)
+    probs = torch.softmax(logits, dim=1).cpu().numpy()
+    pred = probs.argmax(1)
+
+    # choose evenly spaced frames where cells are alive
+    T = X.shape[2]
+    alive_t = [t for t in range(T) if am[:, t].any()]
+    if len(alive_t) > args.n_frames:
+        sel = np.linspace(0, len(alive_t) - 1, args.n_frames).round().astype(int)
+        frames = [alive_t[i] for i in sorted(set(sel.tolist()))]
+    else:
+        frames = alive_t
+
+    name_to_idx = {n: i for i, n in enumerate(names)}
+    cells = []
+    for i in range(len(names)):
+        alive_frames = [fi for fi, t in enumerate(frames) if am[i, t]]
+        pos = [[round(float(X[i, 0, t]), 1), round(float(X[i, 1, t]), 1), round(float(X[i, 2, t]), 1)]
+               if am[i, t] else None for t in frames]
+        sizes_alive = [float(X[i, 3, t]) for t in frames if am[i, t]]
+        parent = lineage_parent(names[i])
+        rec = {
+            "name": names[i],
+            "fate": inv[int(pred[i])],
+            "conf": round(float(probs[i, pred[i]]), 3),
+            "size": round(sum(sizes_alive) / len(sizes_alive), 1) if sizes_alive else 0.0,
+            "b": alive_frames[0] if alive_frames else 0,          # birth frame index
+            "p": name_to_idx.get(parent, -1) if parent else -1,   # parent cell index
+            "pos": pos,
+        }
+        if valid[i]:
+            rec["true_fate"] = inv[int(labels[i])]
+            rec["correct"] = bool(pred[i] == labels[i])
+        cells.append(rec)
+
+    # per-frame contact edges (undirected, capped) straight from the model's graph
+    e_src, e_dst, e_t = raw["edge_src"], raw["edge_dst"], raw["edge_t"]
+    edges_per_frame = []
+    for t in frames:
+        m = e_t == t
+        pairs = set()
+        for s, d in zip(e_src[m].tolist(), e_dst[m].tolist()):
+            # keep only co-alive spatial contacts (both endpoints present this frame);
+            # lineage edges to an already-divided parent aren't drawable.
+            if s != d and am[s, t] and am[d, t]:
+                pairs.add((s, d) if s < d else (d, s))
+                if len(pairs) >= args.max_edges:
+                    break
+        edges_per_frame.append([[a, b] for a, b in pairs])
+
+    def load_json(p):
+        p = ckpt / p
+        return json.loads(p.read_text()) if p.exists() else None
+
+    blob = {
+        "embryo": data.source_file,
+        "n_cells": len(names),
+        "frames": frames,
+        "fate_classes": list(FATE_CLASSES),
+        "cells": cells,
+        "edges": edges_per_frame,
+        "metrics": {
+            "history": load_json("history.json"),
+            "per_class_recall": load_json("per_class_recall.json"),
+        },
+        "explainability": {
+            "saliency": load_json("fate_saliency.json"),
+            "interactions": load_json("fate_explainability.json"),
+        },
+    }
+    blob_json = json.dumps(blob)
+    out = REPO_ROOT / "dashboard" / "fate_dashboard_data.json"
+    out.write_text(blob_json, encoding="utf-8")
+    print(f"Wrote {out} ({out.stat().st_size/1024:.0f} KB) | embryo {data.source_file} | "
+          f"{len(names)} cells | {len(frames)} frames {frames}")
+
+    # Inject into the template -> self-contained dashboard/index.html
+    template = REPO_ROOT / "dashboard" / "fate_dashboard.template.html"
+    if template.exists():
+        html = template.read_text(encoding="utf-8").replace("__FATE_DATA__", blob_json)
+        (REPO_ROOT / "dashboard" / "index.html").write_text(html, encoding="utf-8")
+        print(f"Built dashboard/index.html ({len((REPO_ROOT/'dashboard'/'index.html').read_text(encoding='utf-8'))/1024:.0f} KB, self-contained)")
+    else:
+        print(f"Template not found ({template}); skipped index.html build.")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/Spatio-Temporal-Evolution/scripts/extract_fate_explainability.py b/Spatio-Temporal-Evolution/scripts/extract_fate_explainability.py
new file mode 100644
index 0000000..a4d2609
--- /dev/null
+++ b/Spatio-Temporal-Evolution/scripts/extract_fate_explainability.py
@@ -0,0 +1,166 @@
+"""
+Fate-aware explainability for the trained ESTGEL node classifier.
+
+Runs the fate model over an embryo and, at every recurrence step, reads the EAM
+edge attention + the DRL relation strength on each cell-cell edge. Each edge is
+annotated with the PREDICTED fate of its endpoints, so we can answer the proposal's
+core question: which tissue-tissue interactions the model weights while deciding fate.
+
+Outputs (to checkpoints/estgel_fate/):
+  fate_explainability.json  - per-cell fate predictions + tissue-pair interaction stats
+  fate_interaction_map.png  - tissue x tissue contact-count and mean-attention heatmaps
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+import numpy as np
+import torch
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(REPO_ROOT))
+
+from src.cell_fate import FATE_CLASSES, build_fate_index, fate_targets, load_fate_csv
+from src.epic_dataset import EpicEmbryoDataset
+from src.estgel_node import ESTGELNodeClassifier
+
+
+def load_model(cfg, device):
+    drl = {"Lz": cfg.get("drl_channels") or 12, "Lr": cfg.get("drl_channels") or 12,
+           "Lh": cfg.get("drl_channels") or 12} if cfg.get("drl_channels") else {}
+    m = ESTGELNodeClassifier(
+        num_classes=len(FATE_CLASSES), K=cfg["K"], in_dim=5,
+        recurrence_stride=cfg["recurrence_stride"], max_steps=cfg["max_steps"],
+        bptt_truncation=cfg["bptt_truncation"], max_nodes=cfg["max_nodes"], **drl,
+    ).to(device)
+    m.load_state_dict(torch.load(REPO_ROOT / "checkpoints" / "estgel_fate" / "best.pt",
+                                 map_location=device)["model_state_dict"])
+    m.eval()
+    return m
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--embryo", type=str, default=None, help="npz filename; default = first")
+    ap.add_argument("--top-k", type=int, default=15)
+    args = ap.parse_args()
+
+    ckpt_dir = REPO_ROOT / "checkpoints" / "estgel_fate"
+    cfg = json.loads((ckpt_dir / "config.json").read_text())
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    fi = build_fate_index(); inv = {v: k for k, v in fi.items()}
+    cell_fate = load_fate_csv()
+
+    ds = EpicEmbryoDataset(cfg["processed_dir"], use_global_index=False)
+    idx = ds.filenames.index(args.embryo) if args.embryo else 0
+    data = ds[idx]
+    names = [str(c) for c in data.idx_to_cell]
+    labels, valid = fate_targets(data.idx_to_cell, cell_fate, fi)
+
+    model = load_model(cfg, device)
+    with torch.no_grad():
+        logits, collected, timesteps = model(data)
+    probs = torch.softmax(logits, dim=1).cpu().numpy()
+    pred = logits.argmax(1).cpu().numpy()
+
+    # --- per-cell predictions ---
+    per_cell = []
+    correct = tot = 0
+    for i in range(len(names)):
+        rec = {"cell": names[i], "pred_fate": inv[int(pred[i])],
+               "confidence": round(float(probs[i, pred[i]]), 4)}
+        if valid[i]:
+            rec["true_fate"] = inv[int(labels[i])]
+            rec["correct"] = bool(pred[i] == labels[i])
+            tot += 1; correct += int(pred[i] == labels[i])
+        per_cell.append(rec)
+
+    # --- tissue x tissue attention + contact aggregation over all steps ---
+    C = len(FATE_CLASSES)
+    att_sum = np.zeros((C, C)); cnt = np.zeros((C, C))
+    edge_records = []  # (weight, t, src, dst, src_fate, dst_fate)
+    for out, t in zip(collected, timesteps):
+        ei = out.eam.edge_index.cpu().numpy()
+        ew = out.eam.edge_weights.cpu().numpy()
+        for e in range(ei.shape[1]):
+            s, d = int(ei[0, e]), int(ei[1, e])
+            fs, fd = int(pred[s]), int(pred[d])
+            w = float(ew[e])
+            att_sum[fs, fd] += w; cnt[fs, fd] += 1
+            edge_records.append((w, int(t), names[s], names[d], inv[fs], inv[fd]))
+    mean_att = np.where(cnt > 0, att_sum / np.maximum(cnt, 1), 0.0)
+
+    # top attended interactions (dedup by cell pair, keep max weight)
+    edge_records.sort(key=lambda r: r[0], reverse=True)
+    seen = set(); top = []
+    for w, t, s, d, fs, fd in edge_records:
+        key = (s, d)
+        if key in seen:
+            continue
+        seen.add(key)
+        top.append({"src": s, "dst": d, "src_fate": fs, "dst_fate": fd,
+                    "attention": round(w, 5), "timestep": t})
+        if len(top) >= args.top_k:
+            break
+
+    present = [c for c in range(C) if cnt[c].sum() + cnt[:, c].sum() > 0]
+    report = {
+        "embryo": data.source_file,
+        "n_cells": len(names),
+        "accuracy_on_labeled": round(correct / max(tot, 1), 4),
+        "n_labeled": tot,
+        "recurrence_timesteps": timesteps,
+        "edge_attention_range": [round(float(min(r[0] for r in edge_records)), 4),
+                                  round(float(max(r[0] for r in edge_records)), 4)] if edge_records else None,
+        "tissue_pairs_present": [inv[c] for c in present],
+        "top_interactions": top,
+        "contact_counts": {inv[a]: {inv[b]: int(cnt[a, b]) for b in present if cnt[a, b] > 0}
+                            for a in present},
+        "mean_attention": {inv[a]: {inv[b]: round(float(mean_att[a, b]), 5)
+                                    for b in present if cnt[a, b] > 0} for a in present},
+        "per_cell": per_cell,
+    }
+    out_json = ckpt_dir / "fate_explainability.json"
+    out_json.write_text(json.dumps(report, indent=2), encoding="utf-8")
+
+    # --- heatmap figure ---
+    try:
+        import matplotlib
+        matplotlib.use("Agg")
+        import matplotlib.pyplot as plt
+        lab = [inv[c] for c in present]
+        sub_cnt = cnt[np.ix_(present, present)]
+        sub_att = mean_att[np.ix_(present, present)]
+        fig, axes = plt.subplots(1, 2, figsize=(15, 6.5), dpi=140)
+        for ax, mat, title, cmap in [
+            (axes[0], np.log1p(sub_cnt), "log(1+contact count)  src -> dst", "viridis"),
+            (axes[1], sub_att, "mean EAM attention  src -> dst", "magma"),
+        ]:
+            im = ax.imshow(mat, cmap=cmap, aspect="auto")
+            ax.set_xticks(range(len(lab))); ax.set_xticklabels(lab, rotation=45, ha="right", fontsize=9)
+            ax.set_yticks(range(len(lab))); ax.set_yticklabels(lab, fontsize=9)
+            ax.set_xlabel("destination fate"); ax.set_ylabel("source fate")
+            ax.set_title(title, fontsize=11, fontweight="bold")
+            fig.colorbar(im, ax=ax, fraction=0.046, pad=0.04)
+        fig.suptitle(f"ESTGEL fate-interaction map — {data.source_file} "
+                     f"(acc {report['accuracy_on_labeled']:.2f})", fontsize=13, fontweight="bold")
+        fig.tight_layout()
+        fig.savefig(ckpt_dir / "fate_interaction_map.png", bbox_inches="tight")
+        plt.close(fig)
+    except Exception as e:
+        print("figure skipped:", e)
+
+    print(f"Embryo {data.source_file} | cells {len(names)} | acc {report['accuracy_on_labeled']:.3f}")
+    print(f"EAM attention range: {report['edge_attention_range']}")
+    print("Tissue pairs present:", report["tissue_pairs_present"])
+    print("\nTop attended interactions (src[fate] -> dst[fate]  attn):")
+    for t in top[:args.top_k]:
+        print(f"  {t['src']:14}[{t['src_fate']:10}] -> {t['dst']:14}[{t['dst_fate']:10}]  {t['attention']:.4f} @t{t['timestep']}")
+    print(f"\nSaved: {out_json.name}, fate_interaction_map.png")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/Spatio-Temporal-Evolution/scripts/saliency_fate.py b/Spatio-Temporal-Evolution/scripts/saliency_fate.py
new file mode 100644
index 0000000..76e7761
--- /dev/null
+++ b/Spatio-Temporal-Evolution/scripts/saliency_fate.py
@@ -0,0 +1,204 @@
+"""
+Causal saliency / ablation explainability for the ESTGEL fate model.
+
+The EAM attention is near-saturated, so instead of reading attention magnitudes we
+PERTURB inputs and measure how the predicted-fate probability responds:
+
+  1. Feature occlusion  - mean-impute each input feature (x,y,z,size,blot) and measure
+     the drop in P(predicted fate) per cell -> which features drive each tissue.
+  2. Graph ablation      - remove ALL cell-cell edges and re-predict -> does the model
+     actually use interactions for fate, or is it position alone?
+  3. Gradient saliency   - |d logit_pred / d feature| as an independent cross-check.
+
+Aggregated over several embryos. Outputs to checkpoints/estgel_fate/:
+  fate_saliency.json, fate_saliency.png
+"""
+from __future__ import annotations
+
+import argparse
+import copy
+import json
+import sys
+from collections import defaultdict
+from pathlib import Path
+
+import numpy as np
+import torch
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(REPO_ROOT))
+
+from src.cell_fate import FATE_CLASSES, build_fate_index, fate_targets, load_fate_csv
+from src.epic_dataset import EpicEmbryoDataset
+from src.estgel_node import ESTGELNodeClassifier
+
+FEATURES = ["x", "y", "z", "size", "blot"]
+
+
+def load_model(cfg, device):
+    drl = {}
+    if cfg.get("drl_channels"):
+        drl = {"Lz": cfg["drl_channels"], "Lr": cfg["drl_channels"], "Lh": cfg["drl_channels"]}
+    m = ESTGELNodeClassifier(
+        num_classes=len(FATE_CLASSES), K=cfg["K"], in_dim=5,
+        recurrence_stride=cfg["recurrence_stride"], max_steps=cfg["max_steps"],
+        bptt_truncation=cfg["bptt_truncation"], max_nodes=cfg["max_nodes"], **drl,
+    ).to(device)
+    m.load_state_dict(torch.load(REPO_ROOT / "checkpoints" / "estgel_fate" / "best.pt",
+                                 map_location=device)["model_state_dict"])
+    m.eval()
+    return m
+
+
+@torch.no_grad()
+def predict_probs(model, data):
+    logits, _, _ = model(data.clone())
+    return torch.softmax(logits, dim=1)
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--n-embryos", type=int, default=6)
+    ap.add_argument("--max-cells", type=int, default=1000)
+    args = ap.parse_args()
+
+    ckpt = REPO_ROOT / "checkpoints" / "estgel_fate"
+    cfg = json.loads((ckpt / "config.json").read_text())
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    fi = build_fate_index(); inv = {v: k for k, v in fi.items()}
+    cell_fate = load_fate_csv()
+    model = load_model(cfg, device)
+
+    ds = EpicEmbryoDataset(cfg["processed_dir"], use_global_index=False)
+    # pick small embryos for tractable repeated forwards
+    sizes = [(i, len(np.load(ds.processed_dir / ds.filenames[i], allow_pickle=True)["idx_to_cell"]))
+             for i in range(len(ds))]
+    chosen = [i for i, n in sorted(sizes, key=lambda x: x[1]) if n <= args.max_cells][:args.n_embryos]
+
+    occ = defaultdict(lambda: np.zeros(len(FEATURES)))  # fate -> summed conf-drop per feature
+    occ_n = defaultdict(int)
+    grad_imp = defaultdict(lambda: np.zeros(len(FEATURES)))
+    grad_n = defaultdict(int)
+    # graph ablation accumulators
+    abl_drop = defaultdict(float); abl_n = defaultdict(int); flips = 0; flip_tot = 0
+    acc_full = acc_noedge = acc_tot = 0
+
+    for idx in chosen:
+        data0 = ds[idx]
+        labels, valid = fate_targets(data0.idx_to_cell, cell_fate, fi)
+        P0 = predict_probs(model, data0).cpu().numpy()
+        pred = P0.argmax(1)
+        rows = np.arange(len(pred))
+        p_pred = P0[rows, pred]
+
+        # accuracy full
+        vm = valid
+        acc_full += int((pred[vm] == labels[vm]).sum()); acc_tot += int(vm.sum())
+
+        # ---- feature occlusion (set feature to its train mean => normalized 0) ----
+        fmean = model.feat_mean.cpu().numpy()
+        for k in range(len(FEATURES)):
+            d = ds[idx]
+            d.x[:, k, :] = float(fmean[k])
+            Pk = predict_probs(model, d).cpu().numpy()
+            drop = p_pred - Pk[rows, pred]           # confidence lost when feature removed
+            for i in range(len(pred)):
+                f = inv[int(pred[i])]
+                occ[f][k] += float(drop[i]);
+            for i in range(len(pred)):
+                occ_n[inv[int(pred[i])]] += 1 if k == 0 else 0
+        # normalize occ_n counts (added once per node above only at k==0)
+
+        # ---- graph ablation: remove all edges ----
+        d = ds[idx]
+        d.edge_index = torch.empty((2, 0), dtype=torch.long)
+        d.edge_t = torch.empty((0,), dtype=torch.long)
+        Pne = predict_probs(model, d).cpu().numpy()
+        pred_ne = Pne.argmax(1)
+        drop = p_pred - Pne[rows, pred]
+        for i in range(len(pred)):
+            abl_drop[inv[int(pred[i])]] += float(drop[i]); abl_n[inv[int(pred[i])]] += 1
+        flips += int((pred_ne != pred).sum()); flip_tot += len(pred)
+        acc_noedge += int((pred_ne[vm] == labels[vm]).sum())
+
+        # ---- gradient saliency ----
+        try:
+            d = ds[idx]
+            x = d.x.clone().to(device).requires_grad_(True)
+            d.x = x
+            logits, _, _ = model(d)
+            sel = logits[rows, pred]                  # predicted-class logit per node
+            sel.sum().backward()
+            g = x.grad.abs().to(device)               # (N,d,T)
+            am = d.alive_mask.to(device).float()
+            gpf = (g * am.unsqueeze(1)).sum(2) / am.sum(1, keepdim=True).clamp(min=1)  # (N,d)
+            gpf = gpf.detach().cpu().numpy()
+            for i in range(len(pred)):
+                f = inv[int(pred[i])]
+                grad_imp[f] += gpf[i]; grad_n[f] += 1
+        except Exception as e:
+            print("grad saliency skipped:", e)
+
+    # aggregate
+    def norm_dict(dsum, dcnt):
+        return {f: (dsum[f] / max(dcnt[f], 1)).tolist() if hasattr(dsum[f], 'tolist')
+                else dsum[f] / max(dcnt[f], 1) for f in dsum}
+
+    occ_mean = {f: (occ[f] / max(occ_n[f], 1)).round(4).tolist() for f in occ}
+    grad_mean = {f: (grad_imp[f] / max(grad_n[f], 1)).round(4).tolist() for f in grad_imp}
+    abl_mean = {f: round(abl_drop[f] / max(abl_n[f], 1), 4) for f in abl_drop}
+
+    report = {
+        "embryos_used": [ds.filenames[i] for i in chosen],
+        "features": FEATURES,
+        "accuracy_full": round(acc_full / max(acc_tot, 1), 4),
+        "accuracy_no_edges": round(acc_noedge / max(acc_tot, 1), 4),
+        "prediction_flip_rate_no_edges": round(flips / max(flip_tot, 1), 4),
+        "feature_occlusion_confdrop_by_fate": occ_mean,
+        "graph_ablation_confdrop_by_fate": abl_mean,
+        "gradient_saliency_by_fate": grad_mean,
+    }
+    (ckpt / "fate_saliency.json").write_text(json.dumps(report, indent=2), encoding="utf-8")
+
+    # ---- figure ----
+    try:
+        import matplotlib; matplotlib.use("Agg"); import matplotlib.pyplot as plt
+        fates = [f for f in ["neuron", "muscle", "hypodermis", "pharynx", "intestine"] if f in occ_mean]
+        M = np.array([occ_mean[f] for f in fates])          # (F_fates, 5 features)
+        fig, ax = plt.subplots(1, 2, figsize=(15, 6), dpi=140,
+                               gridspec_kw={"width_ratios": [3, 1]})
+        im = ax[0].imshow(M, cmap="RdBu_r", aspect="auto",
+                          vmin=-np.abs(M).max(), vmax=np.abs(M).max())
+        ax[0].set_xticks(range(len(FEATURES))); ax[0].set_xticklabels(FEATURES)
+        ax[0].set_yticks(range(len(fates))); ax[0].set_yticklabels(fates)
+        ax[0].set_title("Feature occlusion: confidence drop when feature removed\n(red = feature supports the fate)",
+                        fontsize=11, fontweight="bold")
+        for i in range(len(fates)):
+            for j in range(len(FEATURES)):
+                ax[0].text(j, i, f"{M[i,j]:.2f}", ha="center", va="center", fontsize=9)
+        fig.colorbar(im, ax=ax[0], fraction=0.046, pad=0.04)
+
+        gfates = [f for f in fates if f in abl_mean]
+        ax[1].barh(gfates, [abl_mean[f] for f in gfates], color="#c0504d")
+        ax[1].set_title("Graph ablation:\nconf drop with NO edges", fontsize=11, fontweight="bold")
+        ax[1].axvline(0, color="k", lw=0.8)
+        fig.suptitle(f"ESTGEL fate saliency  |  acc full {report['accuracy_full']:.2f} -> "
+                     f"no-edges {report['accuracy_no_edges']:.2f}  (flip {report['prediction_flip_rate_no_edges']:.0%})",
+                     fontsize=13, fontweight="bold")
+        fig.tight_layout(); fig.savefig(ckpt / "fate_saliency.png", bbox_inches="tight"); plt.close(fig)
+    except Exception as e:
+        print("figure skipped:", e)
+
+    print(f"Embryos: {len(chosen)} | acc full {report['accuracy_full']:.3f} -> "
+          f"no-edges {report['accuracy_no_edges']:.3f} | flip rate {report['prediction_flip_rate_no_edges']:.3f}")
+    print("\nFeature occlusion (conf drop when removed) by fate:")
+    print(f"  {'fate':11}" + "".join(f"{f:>8}" for f in FEATURES))
+    for f in ["neuron", "muscle", "hypodermis", "pharynx", "intestine"]:
+        if f in occ_mean:
+            print(f"  {f:11}" + "".join(f"{v:>8.3f}" for v in occ_mean[f]))
+    print("\nGraph-ablation conf drop by fate:", abl_mean)
+    print("Saved fate_saliency.json, fate_saliency.png")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/Spatio-Temporal-Evolution/scripts/train_fate.py b/Spatio-Temporal-Evolution/scripts/train_fate.py
new file mode 100644
index 0000000..3b4221e
--- /dev/null
+++ b/Spatio-Temporal-Evolution/scripts/train_fate.py
@@ -0,0 +1,262 @@
+"""
+Train the ESTGEL node-level cell-fate classifier on EPIC embryos.
+
+Targets come from Dataset/fate/cell_fate.csv (see scripts/build_cell_fate.py).
+Only cells with a usable fate (not 'mixed'/'unknown') contribute to the loss.
+The cell NAME is never a feature — fate is predicted from spatio-temporal signal
+(x, y, z, size, blot + graph dynamics) only.
+
+Split is by embryo (held-out embryos), so validation measures whether the learned
+spatio-temporal features generalise to unseen embryos. Reports accuracy, macro-F1,
+and per-class recall (accuracy alone is misleading under class imbalance).
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import random
+import sys
+import time
+from collections import Counter
+from pathlib import Path
+
+import numpy as np
+import torch
+import torch.nn.functional as F
+from tqdm import tqdm
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(REPO_ROOT))
+
+from src.cell_fate import FATE_CLASSES, build_fate_index, fate_targets, load_fate_csv
+from src.epic_dataset import EpicEmbryoDataset
+from src.estgel_layers import count_parameters
+from src.estgel_node import ESTGELNodeClassifier, compute_feature_stats
+
+
+def build_targets(dataset: EpicEmbryoDataset, cell_fate, fate_index):
+    """Precompute (labels, valid) per embryo, aligned to each embryo's node order."""
+    out = []
+    for i in range(len(dataset)):
+        idx_to_cell = np.load(
+            dataset.processed_dir / dataset.filenames[i], allow_pickle=True
+        )["idx_to_cell"]
+        labels, valid = fate_targets(idx_to_cell, cell_fate, fate_index)
+        out.append((labels, valid))
+    return out
+
+
+def global_class_weights(targets, num_classes, present_ids, cap: float = 5.0):
+    """Mild sqrt-inverse-frequency weights, normalised to mean 1 and capped.
+
+    Raw inverse frequency gives ultra-rare classes (e.g. coelomocyte ~0.2%) 100x+
+    the weight of common ones, which makes the model predict rare classes
+    everywhere and collapses accuracy. The sqrt softens this; the cap bounds it.
+    """
+    counts = torch.zeros(num_classes)
+    for labels, valid in targets:
+        for c in labels[valid]:
+            counts[c] += 1
+    w = torch.zeros(num_classes)
+    inv = torch.zeros(len(present_ids))
+    for i, c in enumerate(present_ids):
+        inv[i] = (1.0 / counts[c].clamp(min=1.0)).sqrt()
+    inv = inv / inv.mean()          # mean-1 normalise
+    inv = inv.clamp(max=cap)        # bound the largest weight
+    for i, c in enumerate(present_ids):
+        w[c] = inv[i]
+    return w
+
+
+@torch.no_grad()
+def evaluate(model, dataset, val_idx, targets, device, num_classes):
+    model.eval()
+    conf = torch.zeros(num_classes, num_classes, dtype=torch.long)
+    loss_sum, n = 0.0, 0
+    for i in val_idx:
+        data = dataset[i]
+        labels, valid = targets[i]
+        if not valid.any():
+            continue
+        logits, _, _ = model(data)
+        y = torch.tensor(labels, device=device)
+        vmask = torch.tensor(valid, device=device)
+        loss_sum += F.cross_entropy(logits[vmask], y[vmask]).item()
+        n += 1
+        pred = logits[vmask].argmax(1).cpu()
+        yv = y[vmask].cpu()
+        for t, p in zip(yv.tolist(), pred.tolist()):
+            conf[t, p] += 1
+    correct = conf.diag().sum().item()
+    total = conf.sum().item()
+    acc = correct / max(total, 1)
+    # macro-F1 over classes that appear as a true label
+    f1s = []
+    for c in range(num_classes):
+        tp = conf[c, c].item()
+        fp = conf[:, c].sum().item() - tp
+        fn = conf[c, :].sum().item() - tp
+        if tp + fn == 0:
+            continue
+        prec = tp / (tp + fp) if tp + fp else 0.0
+        rec = tp / (tp + fn) if tp + fn else 0.0
+        f1s.append(2 * prec * rec / (prec + rec) if prec + rec else 0.0)
+    macro_f1 = sum(f1s) / len(f1s) if f1s else 0.0
+    return {"loss": loss_sum / max(n, 1), "acc": acc, "macro_f1": macro_f1, "n": n}, conf
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--processed-dir", type=Path, default=REPO_ROOT / "Dataset" / "processed" / "by_embryo")
+    ap.add_argument("--fate-csv", type=Path, default=REPO_ROOT / "Dataset" / "fate" / "cell_fate.csv")
+    ap.add_argument("--epochs", type=int, default=15)
+    ap.add_argument("--lr", type=float, default=1e-3)
+    ap.add_argument("--weight-decay", type=float, default=1e-4)
+    ap.add_argument("--val-ratio", type=float, default=0.2)
+    ap.add_argument("--seed", type=int, default=42)
+    ap.add_argument("--max-samples", type=int, default=None)
+    # ESTGEL recurrence is strided across the FULL developmental time so every cell
+    # (incl. late-born) is captured; each cell is pooled over its own alive steps.
+    ap.add_argument("--recurrence-stride", type=int, default=8)
+    ap.add_argument("--max-steps", type=int, default=32)
+    ap.add_argument("--bptt-truncation", type=int, default=6)
+    ap.add_argument("--K", type=int, default=11)
+    ap.add_argument("--max-nodes", type=int, default=2500)  # max embryo has 2434 cells
+    ap.add_argument("--max-cells", type=int, default=None,
+                    help="Skip embryos with more than this many cells (VRAM guard; DRL is O(channels*N^2)).")
+    ap.add_argument("--drl-channels", type=int, default=None,
+                    help="Set Lz=Lr=Lh (default 12). Lower => less VRAM/time.")
+    ap.add_argument("--dropout", type=float, default=0.5)
+    ap.add_argument("--no-class-weight", action="store_true")
+    ap.add_argument("--resume", action="store_true", help="warm-start weights from best.pt and continue the run/history")
+    ap.add_argument("--cosine", action="store_true", help="cosine LR decay over this run's epochs")
+    ap.add_argument("--checkpoint-dir", type=Path, default=REPO_ROOT / "checkpoints" / "estgel_fate")
+    ap.add_argument("--device", type=str, default="auto")
+    args = ap.parse_args()
+
+    device = torch.device("cuda" if (args.device == "auto" and torch.cuda.is_available())
+                          else "cpu" if args.device == "auto" else args.device)
+    torch.manual_seed(args.seed)
+    random.seed(args.seed)
+
+    fate_index = build_fate_index()
+    num_classes = len(FATE_CLASSES)
+    cell_fate = load_fate_csv(args.fate_csv)
+
+    dataset = EpicEmbryoDataset(args.processed_dir, use_global_index=False)
+    targets = build_targets(dataset, cell_fate, fate_index)
+
+    indices = list(range(len(dataset)))
+    if args.max_cells is not None:
+        kept = [i for i in indices if len(targets[i][0]) <= args.max_cells]
+        skipped = len(indices) - len(kept)
+        if skipped:
+            print(f"[max-cells={args.max_cells}] skipping {skipped} embryos over the cell cap.")
+        indices = kept
+    if args.max_samples is not None:
+        indices = indices[: args.max_samples]
+    rng = random.Random(args.seed)
+    rng.shuffle(indices)
+    n_val = max(1, int(len(indices) * args.val_ratio))
+    val_idx, train_idx = indices[:n_val], indices[n_val:]
+
+    present_ids = sorted({int(c) for i in indices for c in targets[i][0][targets[i][1]]})
+    inv = {v: k for k, v in fate_index.items()}
+    weights = None if args.no_class_weight else global_class_weights(targets, num_classes, present_ids).to(device)
+
+    drl_kwargs = {}
+    if args.drl_channels is not None:
+        drl_kwargs = {"Lz": args.drl_channels, "Lr": args.drl_channels, "Lh": args.drl_channels}
+    model = ESTGELNodeClassifier(
+        num_classes=num_classes, K=args.K, in_dim=5,
+        recurrence_stride=args.recurrence_stride, max_steps=args.max_steps,
+        bptt_truncation=args.bptt_truncation,
+        max_nodes=args.max_nodes, dropout=args.dropout, **drl_kwargs,
+    ).to(device)
+
+    # Per-feature standardization from the TRAIN split only (saved in checkpoint buffers).
+    fmean, fstd = compute_feature_stats(dataset, train_idx)
+    model.set_feature_stats(fmean, fstd)
+    print(f"Feature stats (train): mean={[round(v,2) for v in fmean.tolist()]} "
+          f"std={[round(v,2) for v in fstd.tolist()]}")
+
+    optimizer = torch.optim.Adam(model.parameters(), lr=args.lr, weight_decay=args.weight_decay)
+    scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=args.epochs) if args.cosine else None
+
+    start_epoch, best_f1, history = 1, -1.0, []
+    if args.resume:
+        ck = args.checkpoint_dir / "best.pt"
+        if ck.exists():
+            prev = torch.load(ck, map_location=device)
+            model.load_state_dict(prev["model_state_dict"])
+            best_f1 = float(prev.get("val_macro_f1", -1.0))
+            hp = args.checkpoint_dir / "history.json"
+            if hp.exists():
+                history = json.loads(hp.read_text())
+                start_epoch = len(history) + 1
+            print(f"Resumed from {ck}: prev best macroF1={best_f1:.3f}, continuing at epoch {start_epoch}")
+        else:
+            print(f"--resume given but {ck} not found; training fresh.")
+
+    args.checkpoint_dir.mkdir(parents=True, exist_ok=True)
+    config = {k: (str(v) if isinstance(v, Path) else v) for k, v in vars(args).items()}
+    (args.checkpoint_dir / "config.json").write_text(json.dumps(config, indent=2), encoding="utf-8")
+
+    print("=" * 72)
+    print("ESTGEL Cell-Fate (node) Training")
+    print("=" * 72)
+    print(f"Device: {device} | embryos: {len(indices)} (train={len(train_idx)}, val={len(val_idx)})")
+    print(f"Classes present: {[inv[c] for c in present_ids]}")
+    print(f"Params: {count_parameters(model):,} | recurrence: stride {args.recurrence_stride}, <= {args.max_steps} steps (full-T, lifetime-pooled)")
+    print()
+
+    for epoch in range(start_epoch, start_epoch + args.epochs):
+        model.train()
+        t0 = time.perf_counter()
+        loss_sum, n = 0.0, 0
+        for i in tqdm(train_idx, desc=f"epoch {epoch}", leave=False):
+            data = dataset[i]
+            labels, valid = targets[i]
+            if not valid.any():
+                continue
+            logits, _, _ = model(data)
+            y = torch.tensor(labels, device=device)
+            vmask = torch.tensor(valid, device=device)
+            loss = F.cross_entropy(logits[vmask], y[vmask], weight=weights)
+            optimizer.zero_grad(set_to_none=True)
+            loss.backward()
+            torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0)
+            optimizer.step()
+            loss_sum += loss.item()
+            n += 1
+        val, conf = evaluate(model, dataset, val_idx, targets, device, num_classes)
+        elapsed = time.perf_counter() - t0
+        row = {"epoch": epoch, "train_loss": loss_sum / max(n, 1),
+               "val_loss": val["loss"], "val_acc": val["acc"],
+               "val_macro_f1": val["macro_f1"], "elapsed_s": elapsed}
+        history.append(row)
+        lr_now = optimizer.param_groups[0]["lr"]
+        print(f"Epoch {epoch:03d} | train loss {row['train_loss']:.3f} | "
+              f"val loss {val['loss']:.3f} acc {val['acc']:.3f} macroF1 {val['macro_f1']:.3f} | "
+              f"lr {lr_now:.1e} | {elapsed:.1f}s")
+        if scheduler:
+            scheduler.step()
+
+        ckpt = {"epoch": epoch, "model_state_dict": model.state_dict(), "config": config,
+                "val_macro_f1": val["macro_f1"]}
+        torch.save(ckpt, args.checkpoint_dir / "last.pt")
+        if val["macro_f1"] >= best_f1:
+            best_f1 = val["macro_f1"]
+            torch.save(ckpt, args.checkpoint_dir / "best.pt")
+            # per-class recall snapshot for the best model
+            rec = {inv[c]: round((conf[c, c] / conf[c].sum()).item(), 3)
+                   for c in range(num_classes) if conf[c].sum() > 0}
+            (args.checkpoint_dir / "per_class_recall.json").write_text(json.dumps(rec, indent=2), encoding="utf-8")
+
+    (args.checkpoint_dir / "history.json").write_text(json.dumps(history, indent=2), encoding="utf-8")
+    print("=" * 72)
+    print(f"Done. Best val macro-F1: {best_f1:.3f} | checkpoints: {args.checkpoint_dir}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/Spatio-Temporal-Evolution/src/cell_fate.py b/Spatio-Temporal-Evolution/src/cell_fate.py
new file mode 100644
index 0000000..ffb3290
--- /dev/null
+++ b/Spatio-Temporal-Evolution/src/cell_fate.py
@@ -0,0 +1,229 @@
+"""
+Cell-fate labels for C. elegans embryo cells (node-level classification targets).
+
+Because the C. elegans lineage is invariant, every named cell has a known terminal
+fate. This module derives a coarse tissue/fate class for any lineage-named cell
+(e.g. "ABalaaaa", "MSaap", "Ea") from the canonical WormAtlas terminal-cell
+descriptions distributed with DevoWorm (``name-function-each-cell``).
+
+Two kinds of cells:
+
+* **Terminal cells** — an exact lineage name in the reference; class comes straight
+  from its free-text description via keyword rules (:data:`FATE_RULES`).
+* **Progenitors** — the internal nodes actually present in EPIC embryos (which trace
+  only to ~350 cells). A progenitor's fate is the **consensus** of the terminal
+  fates of all its lineage descendants (leaves whose normalized lineage name has the
+  progenitor's name as a prefix). ``purity`` records the fraction that agree; cells
+  below :data:`MIXED_PURITY` are labeled ``mixed`` rather than forced into one class.
+
+IMPORTANT (training): fate is a deterministic function of the *cell name*. Do NOT
+feed the name (or a name-derived id) as a model feature — that is trivial label
+leakage. Predict fate from spatio-temporal signal (position, timing, contacts,
+expression) only; use these labels solely as targets.
+"""
+from __future__ import annotations
+
+import re
+from collections import Counter
+from dataclasses import dataclass
+from pathlib import Path
+
+import pandas as pd
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+DEFAULT_REFERENCE = REPO_ROOT / "Dataset" / "fate" / "name-function-each-cell.xlsx"
+DEFAULT_SHEET = "name-function-each-cell"
+
+# Coarse fate taxonomy. `mixed` and `unknown` are assigned by the resolver, not by
+# a description rule, so they are listed separately from FATE_CLASSES-by-keyword.
+FATE_CLASSES: tuple[str, ...] = (
+    "neuron",
+    "muscle",
+    "hypodermis",
+    "pharynx",
+    "intestine",
+    "glia",
+    "germline",
+    "excretory",
+    "coelomocyte",
+    "death",
+    "other",
+    "mixed",
+    "unknown",
+)
+
+# Ordered (first match wins) keyword rules over the lowercased description.
+# Order matters: e.g. "pharyngeal muscle" must resolve to pharynx, not muscle;
+# sheath/socket (glia) must win over the "neuron" it is often described next to.
+FATE_RULES: tuple[tuple[str, tuple[str, ...]], ...] = (
+    ("death", ("programmed cell death", "cell death", "apoptot", "(dies")),
+    ("germline", ("germ line", "germline", "germ cell", "gonad", "distal tip",
+                   "sperm", "oocyte", "spermathec")),
+    ("intestine", ("intestin", "gut")),
+    ("pharynx", ("pharyn", "marginal cell", "pharyngeal")),
+    ("glia", ("sheath", "socket")),
+    ("muscle", ("muscle", "body wall", "body-wall")),
+    ("hypodermis", ("hypoderm", "hyp7", "seam", "epiderm", "syncyti", "tail spike")),
+    ("excretory", ("excretory",)),
+    ("coelomocyte", ("coelom",)),
+    ("neuron", ("neuron", "interneuron", "sensory", "motor", "ganglion",
+                 "nerve", "dopaminerg", "cholinerg", "amphid", "labial",
+                 "cephalic", "ray")),
+)
+
+MIXED_PURITY = 0.6  # below this fraction of agreeing descendants -> "mixed"
+
+# Founder / early cells not resolvable from terminal leaves (they die out or are
+# germline precursors). Explicit fallbacks keyed on exact name.
+FOUNDER_FATE: dict[str, str] = {
+    "P4": "germline", "Z2": "germline", "Z3": "germline",
+    "P0": "other", "P1": "mixed", "P2": "mixed", "P3": "mixed",
+    "EMS": "mixed", "AB": "mixed", "MS": "mixed",
+}
+
+
+def _norm(name: object) -> str:
+    """Normalize a lineage name: strip whitespace (e.g. 'AB plapaaaapp' -> 'ABplapaaaapp')."""
+    return re.sub(r"\s+", "", str(name))
+
+
+def classify_description(description: object) -> str:
+    """Map a free-text terminal-cell description to a coarse fate class."""
+    text = str(description).lower()
+    for fate, keywords in FATE_RULES:
+        if any(k in text for k in keywords):
+            return fate
+    return "other"
+
+
+@dataclass(frozen=True)
+class FateResolution:
+    fate: str
+    method: str      # "founder" | "exact" | "consensus" | "ancestor" | "unknown"
+    purity: float    # 1.0 for exact/founder; consensus fraction otherwise
+    n_leaves: int    # number of terminal descendants considered
+
+
+class CellFateMap:
+    """Resolves any lineage-named cell to a coarse fate class."""
+
+    def __init__(self, leaf_fate: dict[str, str]) -> None:
+        # leaf_fate: normalized terminal lineage name -> fate class
+        self.leaf_fate = leaf_fate
+        self._leaf_items = sorted(leaf_fate.items())
+
+    @classmethod
+    def from_reference(
+        cls,
+        reference_path: str | Path = DEFAULT_REFERENCE,
+        sheet: str = DEFAULT_SHEET,
+    ) -> "CellFateMap":
+        df = pd.read_excel(reference_path, sheet_name=sheet).dropna(subset=["Cell"])
+        leaf_fate: dict[str, str] = {}
+        for _, row in df.iterrows():
+            lin = _norm(row["Lineage Name"])
+            if not lin or "." in lin:
+                # skip post-embryonic sublineage names (e.g. "P9.aapa"); EPIC is embryonic
+                continue
+            leaf_fate[lin] = classify_description(row.get("Description", ""))
+        return cls(leaf_fate)
+
+    def _descendant_leaves(self, name: str) -> list[str]:
+        return [fate for leaf, fate in self._leaf_items if leaf.startswith(name)]
+
+    def resolve(self, cell: str) -> FateResolution:
+        name = _norm(cell)
+        if name in FOUNDER_FATE and name not in self.leaf_fate:
+            return FateResolution(FOUNDER_FATE[name], "founder", 1.0, 0)
+        if name in self.leaf_fate:
+            return FateResolution(self.leaf_fate[name], "exact", 1.0, 1)
+
+        leaves = self._descendant_leaves(name)
+        if leaves:
+            counts = Counter(leaves)
+            top, n_top = counts.most_common(1)[0]
+            purity = n_top / len(leaves)
+            fate = top if purity >= MIXED_PURITY else "mixed"
+            return FateResolution(fate, "consensus", purity, len(leaves))
+
+        # No descendants (sublineage died out): back off to nearest named ancestor.
+        parent = _lineage_parent(name)
+        while parent is not None:
+            if parent in FOUNDER_FATE and parent not in self.leaf_fate:
+                return FateResolution(FOUNDER_FATE[parent], "ancestor", 1.0, 0)
+            pleaves = self._descendant_leaves(parent)
+            if pleaves:
+                counts = Counter(pleaves)
+                top, n_top = counts.most_common(1)[0]
+                purity = n_top / len(pleaves)
+                fate = top if purity >= MIXED_PURITY else "mixed"
+                return FateResolution(fate, "ancestor", purity, len(pleaves))
+            parent = _lineage_parent(parent)
+        return FateResolution("unknown", "unknown", 0.0, 0)
+
+
+# Local copy of the founder/suffix lineage rule (kept in sync with epic_preprocess).
+_FOUNDER_PARENT: dict[str, str] = {
+    "AB": "P0", "P1": "P0", "EMS": "P1", "P2": "P1", "MS": "EMS", "E": "EMS",
+    "C": "P2", "P3": "P2", "D": "P3", "P4": "P3", "Z2": "P4", "Z3": "P4",
+}
+
+
+def _lineage_parent(cell: str) -> str | None:
+    if cell in _FOUNDER_PARENT:
+        return _FOUNDER_PARENT[cell]
+    if cell and cell[-1].isalpha():
+        return cell[:-1]
+    return None
+
+
+def build_fate_index(classes: tuple[str, ...] = FATE_CLASSES) -> dict[str, int]:
+    """Stable fate-name -> integer-id map for model targets."""
+    return {name: i for i, name in enumerate(classes)}
+
+
+DEFAULT_FATE_CSV = REPO_ROOT / "Dataset" / "fate" / "cell_fate.csv"
+
+# Fate ids that are not usable supervision targets (ambiguous / no-signal).
+NON_TARGET_FATES: frozenset[str] = frozenset({"mixed", "unknown"})
+
+
+def load_fate_csv(path: str | Path = DEFAULT_FATE_CSV) -> dict[str, str]:
+    """Load the generated cell -> fate map (cell name -> fate class name)."""
+    df = pd.read_csv(path)
+    return dict(zip(df["cell"].astype(str), df["fate"].astype(str)))
+
+
+def fate_targets(
+    idx_to_cell,
+    cell_fate: dict[str, str],
+    fate_index: dict[str, int] | None = None,
+    *,
+    exclude: frozenset[str] = NON_TARGET_FATES,
+):
+    """
+    Build per-node fate targets aligned to an embryo's node ordering.
+
+    Args:
+        idx_to_cell: sequence of cell-name strings, node index -> name.
+        cell_fate: name -> fate-class-name map (see :func:`load_fate_csv`).
+        fate_index: fate-name -> id map (defaults to :func:`build_fate_index`).
+        exclude: fate names treated as non-targets (masked out of the loss).
+
+    Returns:
+        labels: numpy int64 (N,) fate ids (-1 where no usable label).
+        valid:  numpy bool  (N,) True where the node has a usable target.
+    """
+    import numpy as np
+
+    fate_index = fate_index or build_fate_index()
+    n = len(idx_to_cell)
+    labels = np.full(n, -1, dtype=np.int64)
+    valid = np.zeros(n, dtype=bool)
+    for i, cell in enumerate(idx_to_cell):
+        fate = cell_fate.get(str(cell))
+        if fate is None or fate in exclude:
+            continue
+        labels[i] = fate_index[fate]
+        valid[i] = True
+    return labels, valid
diff --git a/Spatio-Temporal-Evolution/src/embryo_labels.py b/Spatio-Temporal-Evolution/src/embryo_labels.py
new file mode 100644
index 0000000..c2ef038
--- /dev/null
+++ b/Spatio-Temporal-Evolution/src/embryo_labels.py
@@ -0,0 +1,63 @@
+from __future__ import annotations
+
+import csv
+from pathlib import Path
+
+# Heuristic wild-type / control keywords in EPIC filenames (GSoC proposal: WT vs RNAi).
+_CONTROL_KEYWORDS: tuple[str, ...] = (
+    "bright",
+    "norfp",
+    "norfpxx",
+    "norfpyy",
+    "5a_bright",
+    "end1red",
+    "end3",
+    "rw10029",
+)
+
+
+def infer_label_from_filename(filename: str) -> int:
+    """
+    Binary label: 0 = control / wild-type-like, 1 = perturbed / RNAi-like.
+
+    Override with a CSV manifest via ``load_label_map`` when heuristics are insufficient.
+    """
+    low = Path(filename).stem.lower()
+    if any(keyword in low for keyword in _CONTROL_KEYWORDS):
+        return 0
+    return 1
+
+
+def load_label_map(
+    processed_dir: str | Path,
+    manifest_path: str | Path | None = None,
+    labels_csv: str | Path | None = None,
+) -> dict[str, int]:
+    """
+    Build filename -> label mapping.
+
+    If ``labels_csv`` is provided it must contain columns ``filename,label``.
+    Otherwise heuristic labels are inferred from filenames.
+    """
+    processed_dir = Path(processed_dir)
+    if manifest_path is None:
+        manifest_path = processed_dir / "manifest.txt"
+    manifest_path = Path(manifest_path)
+
+    filenames = [
+        line.strip()
+        for line in manifest_path.read_text(encoding="utf-8").splitlines()
+        if line.strip()
+    ]
+
+    label_map = {name: infer_label_from_filename(name) for name in filenames}
+
+    if labels_csv is not None:
+        labels_csv = Path(labels_csv)
+        with labels_csv.open(newline="", encoding="utf-8") as f:
+            reader = csv.DictReader(f)
+            for row in reader:
+                fname = row["filename"].strip()
+                label_map[fname] = int(row["label"])
+
+    return label_map
diff --git a/Spatio-Temporal-Evolution/src/epic_preprocess.py b/Spatio-Temporal-Evolution/src/epic_preprocess.py
index 7b1ea1a..8ac19e7 100644
--- a/Spatio-Temporal-Evolution/src/epic_preprocess.py
+++ b/Spatio-Temporal-Evolution/src/epic_preprocess.py
@@ -12,6 +12,29 @@
 DEFAULT_FEATURES: tuple[str, ...] = ("x", "y", "z", "size", "blot")
 
 
+# C. elegans founder-cell divisions whose daughter names are NOT a simple
+# suffix of the parent (so `cell[:-1]` fails to recover the parent).
+# Maps daughter -> parent. Covers the early AB/P1/EMS/P2/P3/P4 lineage.
+FOUNDER_PARENT: dict[str, str] = {
+    "AB": "P0", "P1": "P0",
+    "EMS": "P1", "P2": "P1",
+    "MS": "EMS", "E": "EMS",
+    "C": "P2", "P3": "P2",
+    "D": "P3", "P4": "P3",
+    "Z2": "P4", "Z3": "P4",
+}
+
+
+def lineage_parent(cell: str) -> str | None:
+    """Return the parent cell name, using the founder map first, then the
+    suffix rule for sublineage names (e.g. ABal -> ABa)."""
+    if cell in FOUNDER_PARENT:
+        return FOUNDER_PARENT[cell]
+    if cell and cell[-1].isalpha():
+        return cell[:-1]
+    return None
+
+
 @dataclass(frozen=True)
 class EpicIndex:
     cell_to_idx: dict[str, int]
@@ -137,10 +160,9 @@ def preprocess_epic_file_sparse(
         for cell in alive_cells:
             if not cell:
                 continue
-            last = cell[-1]
-            if not last.isalpha():
+            parent = lineage_parent(cell)
+            if parent is None:
                 continue
-            parent = cell[:-1]
             if parent in index.cell_to_idx and cell in index.cell_to_idx:
                 p_idx = index.cell_to_idx[parent]
                 c_idx = index.cell_to_idx[cell]
diff --git a/Spatio-Temporal-Evolution/src/estgel_eam.py b/Spatio-Temporal-Evolution/src/estgel_eam.py
index 1f73e54..9d8b393 100644
--- a/Spatio-Temporal-Evolution/src/estgel_eam.py
+++ b/Spatio-Temporal-Evolution/src/estgel_eam.py
@@ -4,6 +4,28 @@
 from scipy.spatial.distance import pdist, squareform
 
 
+# Early C. elegans founder divisions whose daughter names are not a suffix of
+# the parent name. Keeps this module's lineage edges consistent with
+# epic_preprocess.lineage_parent. Maps daughter -> parent.
+FOUNDER_PARENT: dict[str, str] = {
+    "AB": "P0", "P1": "P0",
+    "EMS": "P1", "P2": "P1",
+    "MS": "EMS", "E": "EMS",
+    "C": "P2", "P3": "P2",
+    "D": "P3", "P4": "P3",
+    "Z2": "P4", "Z3": "P4",
+}
+
+
+def lineage_parent(cell: str) -> str | None:
+    """Parent cell name via the founder map first, then the suffix rule."""
+    if cell in FOUNDER_PARENT:
+        return FOUNDER_PARENT[cell]
+    if cell and cell[-1].isalpha():
+        return cell[:-1]
+    return None
+
+
 def initialize_biological_graph(
     df_active: pd.DataFrame,
     cell_to_idx: dict[str, int],
@@ -48,10 +70,9 @@ def initialize_biological_graph(
     for cell in active_cells:
         if not cell:
             continue
-        last = cell[-1]
-        if not last.isalpha():
+        parent = lineage_parent(cell)
+        if parent is None:
             continue
-        parent = cell[:-1]
         if parent in cell_to_idx and cell in cell_to_idx:
             p_idx = cell_to_idx[parent]
             c_idx = cell_to_idx[cell]
diff --git a/Spatio-Temporal-Evolution/src/estgel_node.py b/Spatio-Temporal-Evolution/src/estgel_node.py
new file mode 100644
index 0000000..4401369
--- /dev/null
+++ b/Spatio-Temporal-Evolution/src/estgel_node.py
@@ -0,0 +1,185 @@
+"""
+ESTGEL node-level cell-fate classifier.
+
+Reuses the ESTGEL EAM -> DRL -> DNL timestep block, but instead of pooling to a
+single graph label it keeps the per-node refined states X_hat and predicts a fate
+class for every cell. This matches the reframed target: predict each cell's terminal
+fate from its spatio-temporal dynamics (position, timing, contacts, expression).
+
+Node representation (v2 — lifetime pooling):
+  The ESTGEL recurrence is run STRIDED across the *full* developmental time
+  (t = 0, s, 2s, ... up to T), carrying DRL/DNL state. For each cell i we pool its
+  refined state X_hat[i] over exactly the strided steps where i is alive:
+
+      emb[i] = concat( mean_t alive X_hat[i, t] ,  X_hat[i, last-alive t] )
+
+  This gives every cell a real, informative embedding regardless of when it is born
+  — crucial because ~70% of EPIC cells are born late; a fixed early window leaves
+  them all-zero and forces an all-majority ("neuron") predictor.
+
+IMPORTANT (training): fate is a deterministic function of the *cell name*. Do NOT
+feed the name as a model feature — that is trivial leakage. Predict from position /
+timing / contacts / expression only.
+"""
+from __future__ import annotations
+
+import numpy as np
+import torch
+import torch.nn as nn
+from torch_geometric.data import Data
+
+from src.estgel_layers import DNLOutput, ESTGELTimestepBlock
+
+
+def compute_feature_stats(dataset, indices, in_dim: int = 5):
+    """Per-feature mean/std over alive cells across the given embryos (train split only)."""
+    sums = torch.zeros(in_dim)
+    sqs = torch.zeros(in_dim)
+    cnt = 0
+    for i in indices:
+        z = np.load(dataset.processed_dir / dataset.filenames[i], allow_pickle=True)
+        X = torch.tensor(z["X"], dtype=torch.float32)          # (N, d, T)
+        am = torch.tensor(z["alive_mask"], dtype=torch.bool)    # (N, T)
+        for di in range(in_dim):
+            v = X[:, di, :][am]
+            sums[di] += v.sum()
+            sqs[di] += (v * v).sum()
+        cnt += int(am.sum())
+    mean = sums / max(cnt, 1)
+    var = (sqs / max(cnt, 1) - mean ** 2).clamp(min=1e-12)
+    return mean, var.sqrt()
+
+
+class ESTGELNodeClassifier(nn.Module):
+    def __init__(
+        self,
+        num_classes: int,
+        K: int = 11,
+        in_dim: int = 5,
+        recurrence_stride: int = 8,
+        max_steps: int = 32,
+        bptt_truncation: int = 6,
+        head_hidden: int = 128,
+        dropout: float = 0.5,
+        max_nodes: int = 3072,
+        **block_kwargs,
+    ) -> None:
+        super().__init__()
+        self.num_classes = num_classes
+        self.in_dim = in_dim
+        self.recurrence_stride = recurrence_stride
+        self.max_steps = max_steps
+        self.bptt_truncation = bptt_truncation
+        self.max_nodes = max_nodes
+
+        self.block = ESTGELTimestepBlock(K=K, in_dim=in_dim, max_nodes=max_nodes, **block_kwargs)
+
+        # Per-feature standardization. EPIC stores raw physical values (x,y ~ hundreds,
+        # blot up to ~1e5); without this the linear head explodes and training diverges.
+        # Set from training data via set_feature_stats(); saved in the checkpoint so
+        # inference uses identical stats.
+        self.register_buffer("feat_mean", torch.zeros(in_dim))
+        self.register_buffer("feat_std", torch.ones(in_dim))
+
+        # embedding = ESTGEL X_hat (mean+last) + RAW features (mean+last) + birth/lifespan.
+        # Raw 3D position/expression is the strongest fate signal and legitimate input
+        # (only the cell NAME is off-limits); X_hat carries the learned relational state.
+        node_dim = in_dim * 4 + 2
+        self.head = nn.Sequential(
+            nn.Linear(node_dim, head_hidden),
+            nn.ReLU(),
+            nn.Dropout(dropout),
+            nn.Linear(head_hidden, num_classes),
+        )
+
+    def set_feature_stats(self, mean: torch.Tensor, std: torch.Tensor) -> None:
+        """Install per-feature standardization stats (shape (in_dim,))."""
+        self.feat_mean.copy_(mean.to(self.feat_mean).view(-1))
+        self.feat_std.copy_(std.to(self.feat_std).view(-1).clamp(min=1e-6))
+
+    def _normalize(self, x: torch.Tensor) -> torch.Tensor:
+        """Standardize (N, d, T) features; padding is re-zeroed downstream by alive masks."""
+        return (x - self.feat_mean.view(1, -1, 1)) / self.feat_std.view(1, -1, 1)
+
+    def _recurrence_timesteps(self, data: Data) -> list[int]:
+        """Strided timesteps across the full alive span (each must have live cells)."""
+        T = int(data.T)
+        alive_any = data.alive_mask.any(dim=0)
+        steps = [t for t in range(0, T, max(self.recurrence_stride, 1)) if bool(alive_any[t])]
+        if not steps:
+            return [0]
+        if len(steps) > self.max_steps:  # subsample evenly to bound compute
+            step = (len(steps) - 1) / (self.max_steps - 1)
+            steps = sorted({steps[int(round(i * step))] for i in range(self.max_steps)})
+        return steps
+
+    def _pool_lifetime(
+        self,
+        collected: list[DNLOutput],
+        timesteps: list[int],
+        data: Data,
+        device: torch.device,
+    ) -> torch.Tensor:
+        """Per-node embedding: ESTGEL X_hat (mean+last) ++ raw features (mean+last) ++ birth/lifespan."""
+        N, d = data.x.shape[0], self.in_dim
+        node_dim = d * 4 + 2
+        if not collected:
+            return torch.zeros(N, node_dim, device=device)
+
+        # --- ESTGEL refined state, pooled over the strided steps where the cell is alive ---
+        Xs = torch.stack([o.X_hat for o in collected], dim=0)   # (S, N, d)
+        Al = torch.stack([data.alive_mask[:, t].to(device).float() for t in timesteps], dim=0)  # (S,N)
+        cnt = Al.sum(dim=0).clamp(min=1.0)
+        xhat_mean = (Xs * Al.unsqueeze(-1)).sum(dim=0) / cnt.unsqueeze(-1)
+        S = Xs.shape[0]
+        last_step = (Al * torch.arange(1, S + 1, device=device).float().unsqueeze(1)).argmax(dim=0)
+        xhat_last = Xs[last_step, torch.arange(N, device=device)]
+
+        # --- Raw features, pooled over the FULL alive span (all T; no recurrence needed) ---
+        Xraw = data.x.to(device)                                # (N, d, T)
+        am = data.alive_mask.to(device).float()                 # (N, T)
+        rcnt = am.sum(dim=1).clamp(min=1.0)                     # (N,)
+        raw_mean = (Xraw * am.unsqueeze(1)).sum(dim=2) / rcnt.unsqueeze(1)   # (N, d)
+        Tlen = am.shape[1]
+        last_t = (am * torch.arange(1, Tlen + 1, device=device).float()).argmax(dim=1)  # (N,)
+        raw_last = Xraw[torch.arange(N, device=device), :, last_t]           # (N, d)
+        birth = (am.argmax(dim=1).float() / max(Tlen, 1)).unsqueeze(1)       # (N,1)
+        lifespan = (rcnt / max(Tlen, 1)).unsqueeze(1)                        # (N,1)
+
+        return torch.cat([xhat_mean, xhat_last, raw_mean, raw_last, birth, lifespan], dim=1)
+
+    def forward(
+        self,
+        data: Data,
+        *,
+        mode: str = "sparse",
+    ) -> tuple[torch.Tensor, list[DNLOutput], list[int]]:
+        device = next(self.parameters()).device
+        data = data.to(device)
+        data.x = self._normalize(data.x)  # both the ESTGEL block and pooling read data.x
+
+        timesteps = self._recurrence_timesteps(data)
+        collected: list[DNLOutput] = []
+        A_hat_prev: torch.Tensor | None = None
+        X_hat_prev: torch.Tensor | None = None
+
+        steps_since_detach = 0
+        for t_idx in timesteps:
+            out = self.block.forward_timestep(
+                data, t_idx, A_hat_prev=A_hat_prev, X_hat_prev=X_hat_prev,
+                mode=mode, device=device,
+            )
+            collected.append(out)
+            steps_since_detach += 1
+            detach = (not self.training) or (steps_since_detach >= self.bptt_truncation)
+            if detach:
+                A_hat_prev = out.A_hat.detach()
+                X_hat_prev = out.X_hat.detach()
+                steps_since_detach = 0
+            else:
+                A_hat_prev = out.A_hat
+                X_hat_prev = out.X_hat
+
+        node_emb = self._pool_lifetime(collected, timesteps, data, device)
+        node_logits = self.head(node_emb)  # (N, num_classes)
+        return node_logits, collected, timesteps