Labs Change Audit release integration
Integrated truthful Labs change auditing, SHA-256 fingerprint captures and five new integrity validators into the 130-check production gate.
CHANGELOG ARCHIVE · PAGE 4 OF 7
Entries 151–200, newest first.
Integrated truthful Labs change auditing, SHA-256 fingerprint captures and five new integrity validators into the 130-check production gate.
Added the public change-audit export, schema, inventory registration, checksums and developer/discovery references.
Added server-rendered audit detail for current candidate, review, context, lens and matrix fingerprints without creating review state.
Added a server-rendered noindex Change Audit overview with artifact families, current capture details and explicit historical comparability state.
Defined added, removed, changed and unchanged states only for explicitly retained comparable fingerprint sets; missing history is NOT_COMPARABLE.
Added deterministic fingerprint inputs for review-lens memberships and descriptive coverage-matrix cells.
Added deterministic fingerprint inputs for claim/source context, evidence-gap flags and provenance references without scoring evidence.
Added deterministic fingerprint inputs for read-only review packets, visible signals, checklist keys and mutation boundaries.
Added deterministic fingerprint inputs for public PREDICTED candidate identity and declared heuristic signals.
Established five audit artifact families and the rule that historical changes are never inferred when comparable retained fingerprints do not exist.
Integrated deterministic review lenses and the descriptive coverage matrix into release metadata, snapshots and the expanded 125-check production gate.
Added a public review-lenses export with exact memberships, matrix data, schema, inventory, checksums and developer discovery.
Added a server-rendered noindex category-pair matrix that keeps packet counts and evidence-context counts explicitly descriptive.
Added a server-rendered noindex lens browser for deterministic packet navigation with GET-based lens/value selection.
Created deterministic category-pair matrix cells with packet counts, claim-context presence and explicit coverage-not-performance boundaries.
Exposed deterministic challenge-set membership as navigation rather than benchmark, correctness or failure labels.
Added signal-count and signal-kind review groupings while preserving the no-confidence and no-priority interpretation boundary.
Added deterministic review groupings based on current claim-specific VERIFIED context availability without relation-verification semantics.
Added deterministic category-pair packet groupings as editorial navigation rather than relation evidence.
Established deterministic read-only navigation over the existing review packet set without creating ranking, priority or decision state.
Integrated claim/source review context, gap markers and provenance trails into release metadata, snapshots and the expanded 120-check production gate.
Integrated Review Context into Labs discovery while preserving RESEARCH, noindex, read-only and claim-specific verification boundaries.
Added a public review-context export with schema, inventory, checksums, developer discovery and well-known discovery.
Added per-candidate read-only dossiers for VERIFIED claim scope, registered sources, gap interpretation and deterministic provenance.
Added a server-rendered noindex Review Context Lab overview with descriptive claim/source coverage and explicit no-score boundaries.
Published deterministic candidate-to-review-to-claim-to-source provenance trails without recording editorial decisions.
Added explicit missing-context markers while prohibiting interpretation as negative evidence, rejection, falsification or low confidence.
Linked review packets to public source title, tier, publisher, date and DOI metadata without turning those fields into review scores.
Linked current review packets to existing claim-specific VERIFIED records for either smell while preserving text and scope boundaries.
Established a read-only context layer that brings public evidence into candidate review without verifying or rejecting candidate relations.
Integrated read-only human-review packets and deterministic challenge sets into release metadata, snapshots and the expanded 115-check production gate.
Integrated Review and Challenge Labs into public discovery while preserving RESEARCH, noindex, no-write and evidence-separation boundaries.
Added machine-readable review packets and challenge-set metadata with schemas, inventory, checksums and developer discovery.
Added deterministic rule-boundary, signal-count, category and signal-pattern inspection slices without treating them as benchmarks.
Added server-rendered read-only review packet navigation with visible rubric prompts and no approve, reject, save or submit controls.
Added stable packet sequencing while explicitly separating display order from priority, quality, confidence and probability.
Added category, context and visible-signal contrasts as human inspection aids rather than scientific evidence.
Created reproducible candidate slices for stress-testing the review interface without publishing scientific ground truth or training labels.
Created one transparent review packet per PREDICTED candidate with canonical context, visible signals, rubric prompts and null decisions.
Established a read-only human-review protocol for PREDICTED candidates with zero automatic canonical or VERIFIED promotion.
Integrated deterministic Labs evaluation and reproducibility metadata into the public contract, release snapshot and expanded 110-check production gate.
Made no-ground-truth, no-confidence, no-personalization and no-automatic-promotion boundaries explicit across the evaluation surface.
Registered the Labs evaluation export across inventory, schemas, checksums, developer discovery and public resource contracts.
Added a server-rendered noindex Evaluation Lab for inspecting run manifests, coverage and visible candidate signals.
Published deterministic run inputs, declared rules, stable ordering and reproducibility boundaries for the current candidate set.
Separated descriptive signal counts from confidence, probability, scientific similarity and benchmark-performance claims.
Added descriptive canonical-smell and category-pair coverage counts without treating coverage as quality or scientific validity.
Published visible signal-by-signal explanations for each PREDICTED candidate with an explicit UNREVIEWED review state.
Added a declared run record for the public prediction rule, its inputs, exclusions, ordering and zero promotion effect.
Created the public evaluation model for reproducibility and descriptive audits while keeping SmellBook Labs explicitly RESEARCH.