Commit Graph
3 Commits
Author SHA1 Message Date
Marius CiepluchandClaude Fable 5.1 c8f7610313 fix(types): mypy clean again over src; stub-less libraries and the benchmark imports handled in pyproject
66 errors had accumulated in src since the last green run (the hunt modules of groups 4-6, stats, candidates,
runner). Codex typed them without behaviour change; the 17 inline import-untyped ignores it added are replaced by
one override for dspy, pandas, statsmodels and scikit-learn, and the hunt package's lazy imports of benchmarks/
(never type-checked, not in files) are followed silently so src stays strict against their signatures.

Co-Authored-By: Claude Fable 5.1 <[email protected]>
2026-10-14 03:03:12 +02:00
Marius CiepluchandClaude Fable 5.1 dbaaa86d5b feat(hunt): contamination check (4.5): runs that used a reported repository are marked and kept out of any gain
contamination.py reads the repositories named by the held-out pilot manifest and by every
benchmark report (accepted_repos.json and NOTES.md links under benchmarks/measurements), marks
each run directory clean or contaminated with the report digest and time, and refuses to count
an unchecked run toward a gain. ablation.analyse carries excluded_from_gain when its run is
contaminated. Implemented by Codex (gpt-6-astra), gated here; the benchmark import is lazy so
the package imports without the benchmarks tree.

Co-Authored-By: Claude Fable 5.1 <[email protected]>
2026-10-13 19:03:23 +02:00
Marius CiepluchandClaude Fable 5.1 6e5d060de6 feat(hunt): registered paired ablation, repository folds, leak audit, importance table and the keep/drop rule (4.2-4.4)
ablation.py registers the manifest (table digest, arms as masks, folds, metric, sample, budget,
rule, seed, program id) before any run and refuses a run or an analysis that does not match it.
Arms run over the same changes through runner.run, paired by change; effects on recall and on
suspicions per ordinary push are reported pooled and per family with the repository-clustered
bootstrap and exact McNemar, plus the recall-against-suspicions curve at every reported
confidence (never a tuned cut). The importance table and decisions read held-out effects only;
a neutral annotation survives only when a kept one needs it. 30 fixture tests with a scripted
model. Implemented by Codex (gpt-6-astra), gated here.

Co-Authored-By: Claude Fable 5.1 <[email protected]>
2026-10-13 18:49:58 +02:00