edaphos 1.0.0 — Pillar 1 at paper scale: persistence, RDF export and audit

Summary

First major version: a Knowledge Graph built from tens of thousands
of abstracts is no longer an in-memory dead end. Four additive
capabilities turn Pillar 1 into a research artefact that can be
persisted, federated with external RDF vocabularies, and
interrogated by standard audit primitives.

Persistence

• causal_kg_save() / causal_kg_load() serialise an
  edaphos_causal_kg through its tidy edge list (not through
  igraph's raw C-level pointer layout), so the resulting .rds
  is portable across igraph versions and byte-reproducible.
  Loading reruns the duplicate-edge merge + cycle check so a saved
  KG round-trips exactly to a freshly built one. The header
  carries a format_version tag, a saved_at timestamp and the
  edaphos / R version metadata.

RDF 1.1 Turtle export

• causal_kg_to_turtle() emits a W3C-conformant RDF 1.1 Turtle
  document (Beckett et al. 2014). Each edge becomes a reified
  rdf:Statement carrying confidence, evidence, source(s) and
  timestamp, so the full provenance stack survives the round-trip;
  each node is assigned a stable IRI inside a user-controlled
  namespace so the KG federates cleanly with AGROVOC, ENVO and
  other SKOS thesauri via owl:sameAs. The emitter is pure R — no
  RDF library dependency — and the output parses against any
  RDF 1.1-conformant consumer (rdflib, Jena, Oxigraph, Blazegraph,
  GraphDB, Virtuoso).

Paper-scale audit

• causal_kg_rank_edges(by = c("n_sources", "mean_confidence", "agrovoc_support")) collapses the KG to unique
  (cause, effect) pairs and sorts by a priority list of metrics.
  The single most informative signal for an LLM-extracted KG is
  n_sources — an edge asserted by 50 papers is far more
  trustworthy than one asserted by 1. An optional alignment
  argument attaches agrovoc_cause, agrovoc_effect and
  agrovoc_support columns so the caller can prefer edges whose
  endpoints resolve to community-governed vocabulary.

• summary.edaphos_causal_kg() is the one-line health check:
  node count, edge count, unique source count, confidence
  quartiles, DAG-ness verdict, and the most prolific source.

Concurrent AGROVOC alignment

• causal_ontology_agrovoc_align_batch() dispatches N
  single-term SPARQL queries concurrently through
  httr2::req_perform_parallel() with a user-controlled
  max_active, idempotent on-disk cache, and exponential-backoff
  retries. Measured speedup of roughly 5× at max_active = 5
  against agrovoc.fao.org, with warm-cache re-runs ~3700× faster
  than cold.

  A note on the batching strategy: true SPARQL-level batching
  (VALUES + CONTAINS(?label, ?term)) is rejected by AGROVOC's
  production endpoint with a 504 gateway timeout because the
  substring filter cannot short-circuit against a bound term set.
  agrovoc_align_batch() therefore batches at the transport layer
  instead — identical on-wire semantics, only the wall-clock time
  changes.

• causal_kg_alignment(kg, vocab = "agrovoc", agrovoc_batch = TRUE, agrovoc_max_active = 5L) is the KG-level one-liner that
  routes the batched resolver through the standard alignment
  output.

Documentation

• Vignette pilar1-causal gains §11 "Paper-scale audit:
  persistence, Turtle, ranked edges" deriving each primitive from
  first principles with reproducible toy-KG examples.
• README gains a "Paper-scale persistence, Turtle export and
  multi-source audit" subsection with a complete save → Turtle →
  align → rank walk-through.

Quality

• 62 new tests land in test-causal-v10.R covering the RDS
  round-trip, the Turtle emitter (prefix declarations, reified
  edges, escape rules, empty-KG handling), the ranker
  (multi-key sort, AGROVOC support, top_n), summary() and the
  mocked parallel-dispatch variant.
• Full causal test suite: 167 / 167 green.
• R CMD check --as-cran: 0 errors / 0 warnings / 2 harmless
  NOTEs (network timestamp + PySCF tempdir carried over from
  v0.9.0).