Persistent-learning diagnosis: six frozen phase orders audited

Publishes #84's frozen six-order comparison, measured at f4b97fd / code-v95. All 8,640 episodes were independently replayed; seven semantic/provenance controls were rejected. Original-order traces, acceptance and weight hashes exactly match the prior 1,440-row pilot.

At budget 144, persistent SNN accepts 378/864 repeated task/order/seed attempts versus frozen 395 and reset 415. Persistent learning loses to reset in four orders, wins one and ties one; pooled first-choice counts equal frozen. All frozen gates fail. This supports further mechanism work, not the claim that persistence loses in every order.

At full grammar, reset uses 14.2% fewer pooled candidates than streaming, with fewer candidates in all 18 order/seed runs, but 3.56 times its CPU. Persistent saves 1.5% pooled candidates with mixed per-run results and 4.04 times streaming CPU. No total-work or hardware-energy gain is established.

Validation remains 46 affected and 420 fast tests passed with unchanged source hashes, no skips/exclusions. Slow/retry and local full discovery were not run for this additive diagnostic. The measured source's CI run 39164398208 is separate from earlier source scopes; full CI is not credited as passing. #84 remains open for mechanism and sensor/hardware work.