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Evals: expand golden set to fourteen domains-spanning queries, add JSON report output - #41

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evals/golden-set-expansion
Sep 2, 2026
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Evals: expand golden set to fourteen domains-spanning queries, add JSON report output#41
Ndevu12 merged 1 commit into
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evals/golden-set-expansion

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@Ndevu12 Ndevu12 commented Sep 1, 2026

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Summary

Roadmap follow-up on the evaluation harness: the golden dataset more than doubles — six queries to fourteen, spanning seven fields — so domain-agnostic ranking quality is finally measured, not assumed. The harness also gains a JSON output mode for automation.

Dataset expansion

Eight new labeled queries with graded relevance and deliberate cross-domain hard negatives:

  • federated learning privacy preservation (ML)
  • protein structure prediction with deep learning (biomedicine)
  • sleep deprivation effects on memory and cognition (neuroscience)
  • misinformation spread on social media (social science)
  • quantum error correction codes (physics)
  • end-to-end deep learning speech recognition (speech)
  • gut microbiome influence on brain and behavior (biomedicine)
  • generative adversarial networks image synthesis (computer vision)

Dataset integrity policy holds throughout: every candidate is a real paper, and entries whose DOI cannot be stated with confidence carry no DOI rather than a guessed one — the same fabricated-metadata discipline the pipeline itself enforces. Two high-confidence DOIs were added to keep citation validity comfortably above the CI floor.

Measured baseline (keyword-only, fourteen queries)

Metric Value CI floor
mean R@5 0.94 ≥ 0.80
mean R@10 1.00
mean nDCG@10 0.97 ≥ 0.85
mean MRR 1.00 ≥ 0.85
citation validity 92% ≥ 0.90

All regression floors hold unchanged; the added domains put real headroom pressure on the ranker (per-query R@5 dips to 0.75 on three queries — exactly the targets the reranker should move).

Harness improvements

  • Table output gains a domain column and a mean R@5 figure.
  • New --json flag on the module entry point emits the full report (per-query metrics plus means) for automation and CI artifacts, backed by format_report_json.
  • Docs and the regression-test baseline text refreshed to the fourteen-query numbers.

Verification

  • pipenv run pytest tests/ — 427 passed (dataset well-formedness now asserts ≥14 queries across ≥6 domains; new JSON round-trip test), 1 skipped
  • ruff check src tests setups — clean; scripts/check_docs_policy.py — passes
  • JSON mode smoke-tested end to end: 14 queries, means match the table above

@Ndevu12 Ndevu12 self-assigned this Sep 2, 2026
@Ndevu12 Ndevu12 added the enhancement New feature or request label Sep 2, 2026
@Ndevu12
Ndevu12 force-pushed the evals/golden-set-expansion branch from 1fa5480 to 25463c9 Compare September 2, 2026 11:24
Grow the evaluation dataset beyond machine learning so domain-agnostic
ranking is actually measured:

- Eight new labeled queries covering federated learning privacy,
  protein structure prediction, sleep and memory, misinformation on
  social media, quantum error correction, end-to-end speech
  recognition, the gut-brain axis, and GAN image synthesis — each with
  graded relevance and cross-domain hard negatives
- Dataset policy holds: entries whose DOI cannot be stated with
  confidence carry none rather than a guessed one; two high-confidence
  DOIs added to keep citation validity comfortably above the CI floor
- Measured keyword-only baseline across fourteen queries: mean R@5
  0.94, R@10 1.00, nDCG@10 0.97, MRR 1.00, citation validity 92% —
  all regression floors hold unchanged
- Harness gains a domain column in the table and a JSON output mode
  (per-query metrics plus means) for automation and CI artifacts,
  exposed via a --json flag on the module entry point
- Docs and test baseline text refreshed to the fourteen-query numbers
@Ndevu12
Ndevu12 force-pushed the evals/golden-set-expansion branch 2 times, most recently from ffc2f4f to 9d09e12 Compare September 2, 2026 13:56
@Ndevu12
Ndevu12 merged commit 0d3860a into main Sep 2, 2026
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