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

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

docs/decision-engine.md

@@ -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