R12 Episodic-Generator Constraint Result

Decision

reject_architecture_native_shohin_reasoning_retain_neurosymbolic_solver

The candidate reaches 11/11 development queries, but adversarial audit rejects promotion as Shohin reasoning. The actual learned system is a 232,065- parameter record-direction classifier feeding exact regex parsing, exhaustive 127-word enumeration, host-side sealing, and a Python executor. The protected Shohin checkpoint is not loaded or called.

The preregistered confirmation does not formally pass every promotion condition. Deranging one support generator produces zero correct answers and zero correct maps, but one of 11 altered episodes still seals a wrong packet; the frozen confirmation required zero seals. Preserve this as a formal gate miss rather than weakening the criterion after seeing the result.

The defensible classification is a bounded neuro-symbolic permutation solver with a learned syntax-orientation frontend. It is not architecture-native program induction and not a Shohin capability.

Protected Base

• checkpoint: train/flagship_out/ckpt_0300000.pt
• protected parameters: 125,081,664
• SHA-256: 211d6b2cddf0c2cf8b12cb0b2d73f9c4440d85f6f531018080c8afd35b2f66a6
• confirmation-time local/Newton hash match: yes
• continuation pretraining: held by explicit user instruction

The checkpoint was not modified, trained, loaded, or executed during this experiment. Adding its parameter count to the conceptual ledger does not make it part of the candidate.

Mechanism

Each episode contains four opaque actions:

1. two complete support-generator transition tables; and
2. two sparse target actions composed from those support generators.

A 232,065-parameter byte reader learns record direction. Exact regex code extracts cardinality, action equality, numeric states, record boundaries, and query actions. Fixed code identifies complete supports by record count, constructs all 127 syntactic words through depth six, applies a finite- temperature match softmax, seals two target tables, and executes the query in Python.

The report's zero search/solver counters do not describe the end-to-end system: 127-word enumeration is exhaustive bounded search and the sealer plus executor are symbolic host algorithms.

Data and Audit

The confirmation board, seed 20260726, contains 26 frozen episodes:

• 15 fitting episodes across cyclic, dihedral, and bitwise families;
• 11 development episodes covering unseen laws, deeper compositions, cardinality 16, held-out renderers, joint shifts, and a completely held-out random-permutation generator family;
• 52 unique target laws;
• zero training/development target-law overlap;
• zero raw target-map overlap;
• 22 development target-word instances, of which 14 overlap training;
• all four abstract length-two words present in both splits;
• 89 sparse target records, all inclusion-minimal;
• 99 hidden query transitions and zero target transitions visible at query time;
• 8/8 renderer orbits compiling to identical packets;
• 26/26 law swaps changing the answer;
• 16/16 eligible action-order reversals changing the answer; and
• 52/52 support keys deleted from deployed packets.

The updated mechanics audit receipt SHA-256 is b29101d13632f1406d51088909607e5a3aa0af043103e51fa8df62c3dd9a0e6d. It is not implementation-independent because it imports the same generator, compiler, decoder, and executor family.

Training used 375 rows:

• 15 frozen fitting rows;
• 60 counterfactual direction rows; and
• 300 auxiliary rows.

One model received 1,000 optimizer updates. All controls reused the same weights with zero additional updates. Training loss fell from 7.5843468 to 0.0000001813.

Confirmation

Newton job 704792 completed on one H100 in 5 minutes 38 seconds.

Treatment is exact in every development cell and family:

• cyclic: 3/3;
• dihedral: 3/3;
• bitwise: 3/3;
• held-out random permutation: 2/2;
• composition: 3/3;
• renderer: 3/3;
• topology: 3/3;
• unseen law: 1/1; and
• joint shift: 1/1.

Every serialized treatment packet excludes literal source and support bytes. This is not process-level deletion: source rows and parsed tensors remain live during query execution and the packet contains a source-derived digest.

The deranged-support arm is causally decisive for accuracy but misses the strong fail-closed criterion: 10/11 packets reject, while one internally consistent but wrong altered episode seals. The treatment capability is therefore demonstrated, but promotion as a universally fail-closed mechanism is withheld.

An independent exact identifiability audit explains this miss. Under the perturbed abstract support/observation interface, six episodes are ambiguous, four are contradictory, and the held-out random-permutation law episode is a coherent alternate world: each target has exactly one surviving program and neither is the original target map. Therefore a constraint compiler operating only on that abstract interface cannot reject all deranged episodes without also rejecting evidence-consistent worlds. Raw-source redundancy remains available and could detect the injected internal corruption, but that would measure a parser checksum rather than law induction. The frozen formal miss is preserved.

The identifiability report is artifacts/r12/episodic_generator_constraint/deranged_identifiability_seed20260726.json; its receipt SHA-256 is 4e48a77c7f3ea9995a36094467585fd99ff2164abc4c89fa0761c3950eb5d8af and file SHA-256 is a58f64bec1f61eb8e9e611e45e525feac54a95b93b211dbb2c1d437800e30292.

Receipts

• report: artifacts/r12/episodic_generator_constraint/seed20260726.json
• report SHA-256: 226a36d9156101617b769f698550eb51ebec57a8ffa01464bdd7a64d8805caad
• model: artifacts/r12/episodic_generator_constraint/seed20260726.pt
• model SHA-256: 37a28b0f9ab401d369e481f99c62393dee99125250dbd6ce1ba37c07e360512f
• focused tests: 14 passed
• Ruff: clean
• byte compilation: clean
• actual trained candidate parameters: 232,065
• protected Shohin parameters participating in the runtime: 0
• conceptual ledger sum only: 125,313,729

Pre-Hardening Canary

Job 704786, seed 20260725, first established 11/11 treatment exactness, including 2/2 held-out random-permutation episodes. Its ambiguous posterior could still accidentally seal 4/11 witness-deletion packets. That result is retained as a mechanics measurement only. Consensus sealing and a regression test corrected the defect before the confirmation run.

Scientific Conclusion

The 11/11 score establishes that a learned renderer-direction classifier plus a bounded symbolic permutation solver works on this board. It does not establish that Shohin learned parsing, law induction, program construction, constraint conjunction, source-deleted execution, or reasoning.

Do not retain this as Shohin's best reasoning baseline. Keep it as a neuro-symbolic mechanics control. The next admissible claim-bearing path must load Shohin, consume raw tokens, eliminate semantic host parsing/search/ execution, enforce process-level deletion, hold out abstract programs, and cross genuinely different ontologies. Full hostile findings are in R12_EPISODIC_GENERATOR_ADVERSARIAL_AUDIT.md.