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feat(learn): A/B experiment runner -- registered manifests, paired arms, bootstrap and McNemar (decision-engine task 7)

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learn/experiments.py: YAML manifests under plane/experiments/<id>.yaml,
digest-checked at register, run and analyse time; `experiment`,
`arm_outcome` and `experiment_result` rows; paired arms in a seeded
repository order with a per-unit coin; arm A replay-only at $0; canary
replicates under a fresh cache salt; repository-cluster paired bootstrap,
exact McNemar, two O'Brien-Fleming looks, adopt/reject/equivalent/
inconclusive. `ousast learn experiment register|units|run|analyse`.
Program: `ProgramSpec.sampling = retrieval_ensemble` (k samples at
temperature 0 over k disjoint retrieved example sets; default unchanged);
`Caller.salt`; `retrieve(exclude=)`. verify: OUSAST_VERIFY_CALLERS=off.
Manifests exp-001-known-callers (plane arms, units pending) and
exp-002-retrieval-ensemble (slice-2 incumbents, ceiling $4) -- not run.
18 scripted tests; module audit regenerated (151 modules).

Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
This commit is contained in:
Marius Ciepluch
2026-10-02 16:04:33 +02:00
co-authored by Claude Fable 5.1
parent a90e570f48
commit fbc3220bbe
14 changed files with 1681 additions and 35 deletions
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docs/decision-engine.md
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@@ -79,6 +79,7 @@ v3 check are still ahead.
| `ousast learn evaluate --program ID` | outer-fold evaluation, cross-fitted calibration, nested operating points |
| `ousast learn curve --program ID` | the metric over memory size on a fixed candidate subset |
| `ousast learn audit-leaks` | how well each signal alone separates the sides of a pair (no model) |
| `ousast learn experiment register\|units\|run\|analyse MANIFEST` | A/B experiments from a pre-registered manifest (`plane/experiments/<id>.yaml`): record its digest, freeze the units (no model), run the arms paired (arm A may replay from the cache at $0), analyse (repository bootstrap, exact McNemar, two looks, the adoption verdict) |
The memory store is the plane's (`OUSAST_MEMORY`; see [ops/ax/README.md](ops/ax/README.md)).
The harvest that produced the plane signals runs as plane Runs generated by
docs/memory.md
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@@ -30,7 +30,10 @@ replaces itself. The kinds (`KINDS`) and who writes them:
| `features` | `remember` task, from the `features` task | one feature record per candidate and family |
| `proposal_outcome` | `ousast improve --memory` (not with `--dry-run`), and the loop's `improve` step | what happened to each memory proposal in a round |
| `example` | `ousast learn memory build` | a labelled case: label + feature record + excerpt sha (no rationale) |
| `label`, `decision`, `experiment`, `arm_outcome`, `experiment_result` | reserved for later decision-engine tasks | declared in `KINDS`; not written by the code on main yet |
| `experiment` | `ousast learn experiment register` (task `register`) and `run` (task `run`) | a registered manifest's digests and provenance; a run's counts-only summary. Repo `experiments/<id>`, pin the registering commit |
| `arm_outcome` | `ousast learn experiment run` | one decision per (unit, arm, replicate): score, verdict, usd, order |
| `experiment_result` | `ousast learn experiment analyse --record` | the paired estimates, the looks and the adoption verdict (counts and intervals only) |
| `label`, `decision` | reserved for later decision-engine tasks | declared in `KINDS`; not written by the code on main yet |
**Blobs** (`put_blob`) are content-addressed: a 64-hex name under a fixed prefix. Excerpts are
written by `learn memory build` (`learn/examples.py`), embeddings by `learn memory embed`