R12 ETTR Isolated Learnability Implementation Audit

Scope

This audit compares R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md with the existing ETTR data contract, objective structures, cross-ontology generators, and structural-variant generators. It addresses deterministic CPU materialization only. It does not authorize training, evaluation, confirmation opening, or Newton execution.

Decision

NO-GO for claim-bearing CPU materialization.

The frozen theory-index pools and existing score-board commitments are reconstructible, but the preregistration does not yet determine a unique dataset. Several required objects have no canonical schema or constructor, some preregistered rectangles are incompatible with ETTRCausalRectangle, and the resource depth/command requirements cannot be satisfied by the current generator. Materializing now would require the implementer to make unregistered scientific choices.

Hard Blockers

1. The split commitments have no reconstructible preimage

Evidence

The preregistration publishes master, split, and fold hashes at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:170-203.
It ranks candidates with SHA256(master_commit || canonical_tuple_bytes) at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:180-187.
It never defines the split-spec bytes, fold-spec bytes, canonical_tuple_bytes, candidate fields, field encodings, candidate domains, or enumeration order.
No existing generator contains those commitments or an ETTR isolated-board constructor.

Impact

A hash authenticates known bytes; it cannot reconstruct an unspecified preimage. Two conforming implementers can produce different folds, strata, and rows while retaining the same prose interpretation.

Required repair

Freeze literal canonical split/fold specification files or an exact constructor for them. Define a versioned tuple schema and byte encoding containing, at minimum: fold, split, ontology, stratum, theory identity, two worlds, two commands, depth, renderer, presentation, query semantics, paraphrases, and opaque-name seed. Define admissibility, complete candidate enumeration, stable sorting, tie handling, and fold-hash derivation.

2. Command depth 4-6 is unsupported, and depth semantics are incomplete

Evidence

The preregistered composition split requires operation-sequence depths 4, 5, 6 at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:112-125.
Resource programs are capped at three operations by MAX_SEQUENCE_LENGTH = 3 in pipeline/cross_ontology_resource_board.py:175-180.
execute_sequence rejects sequences outside lengths 1-3 at pipeline/cross_ontology_resource_board.py:233-243.
Existing resource held-out programs contain only lengths 2 and 3 at pipeline/cross_ontology_resource_board.py:296-302.
Existing factorial commands encode one Horn atom, one rewrite constructor, or one resource sequence at pipeline/ettr_factorial_qualification_board.py:397-404; execution applies those single Horn/rewrite actions at pipeline/ettr_factorial_qualification_board.py:436-466.

Impact

Resource depth 4-6 is rejected by the current oracle. For Horn and rewrite, there is no frozen definition of a dependent multi-operation command, its intermediate states, failure behavior, or transaction trace.

Required repair

Freeze a typed command AST and sequential execution oracle for every ontology, including intermediate packet/transaction targets. Either extend and validate resource execution through depth 6 or preregister a different composition regime. Define Horn and rewrite composition rather than inferring it from single-operation code.

3. The 16-row semantic rectangle is incompatible with the ETTR rectangle contract

Evidence

One preregistered semantic rectangle has 16 rows: four world-command cells, two query semantics, and two paraphrases at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:108-122.
Its admission rule requires each WORLD and COMMAND edge to change at least one of the two query answers at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:115-122.
ETTRCausalRectangle is exactly [R, 2, 2] at train/ettr_data_contract.py:649-669, partitions every row once at train/ettr_data_contract.py:670-682, requires one identical query prefix across all four cells at train/ettr_data_contract.py:743-770, and requires every WORLD and COMMAND edge to change that prefix's label at train/ettr_data_contract.py:771-786.

Impact

A rectangle admitted because query A changes an edge while query B does not is valid under the preregistration but invalid under the ETTR contract. The 16 rows also cannot be represented as one current ETTRCausalRectangle.

Required repair

Choose and freeze one rule. The least invasive repair is to require every selected query-semantic/paraphrase group to satisfy all four ETTR edge contrasts, then expand one semantic rectangle into four explicitly ordered four-row causal rectangles. Otherwise, version and change the data/objective contract under a new protocol.

4. “Rectangle” denotes two different optimization units

Evidence

Dataset sizes count 16-row semantic rectangles at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:143-168.
Optimization uses eight “rectangles” per update and two per microbatch at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:225-240.
The implemented rectangle is the four-row object described in Finding 3.
Six thousand updates times eight rectangles exceeds the 2,304 fitting rectangles, but no epoch, wrap, repetition, or reshuffle schedule is frozen.

Impact

The two readings yield either 128 or 32 rows per update and expose different numbers of query formulations. They therefore change tokens, FLOPs, objective weighting, and the exact training stream.

Required repair

Rename the units semantic_rectangle and causal_rectangle; define their exact expansion and row order. Freeze rows per microbatch/update, accumulation, query grouping, the 6,000-update repeat schedule, end-of-epoch behavior, and whether ranking is reused or rerun.

5. The anonymous typed AST and four renderers do not exist

Evidence

The preregistration requires canonical JSON, prefix S-expression, record-delimited infix, and reverse/postfix renderings of one anonymous typed AST at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:127-134.
Horn currently uses four ontology-specific evidence styles at pipeline/cross_ontology_horn_board.py:298-343.
Rewrite renderings are ontology-specific at pipeline/cross_ontology_rewrite_board.py:611-668.
Resource renderings are ontology-specific at pipeline/cross_ontology_resource_board.py:443-536.
The factorial board only supplies canonical JSON world/command bytes at pipeline/ettr_factorial_qualification_board.py:328-404 and two JSON query forms at pipeline/ettr_factorial_qualification_board.py:407-433.

Impact

There is no shared AST schema, total renderer, parser, round-trip check, or independent semantic equivalence oracle. Renderer assignment and exact bytes cannot be derived.

Required repair

Freeze an ontology-neutral WORLD/COMMAND/QUERY AST with canonical field order and type tags. Implement four total renderers plus independent parsers and round-trip semantic checks. Pin delimiters, escaping, whitespace, integer encoding, templates, and tokenizer identity.

6. Current candidate bytes leak the held-out ontology

Evidence

Stable family/ontology labels are forbidden at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:81-85.
Existing qualification payloads explicitly use numeric domain codes at pipeline/ettr_factorial_qualification_board.py:88-96.
The same stable "d" code is embedded in world, command, and query bytes at pipeline/ettr_factorial_qualification_board.py:328-433.

Impact

The unnamed integer is a perfect ontology identifier. In leave-one-ontology-out scoring it permits family routing and violates the stated isolation rule even though no human-readable family name appears.

Required repair

Remove stable domain codes from candidate-visible bytes and infer types from anonymous syntax, or explicitly allow anonymous domain tags and preregister them as candidate features. In either case, include the exact bytes in leakage controls and metadata-classifier inputs.

7. Rewrite fit presentations cannot be generated

Evidence

Every fit ontology must use base, alpha_reorder, and alias_split at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:136-140.
Rewrite fitting uses the frozen fit theory indices at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:89-95.
build_rewrite_variant_family rejects any theory outside HELDOUT_THEORY_INDICES at pipeline/cross_ontology_rewrite_variants.py:1317-1323.
The emitted variant family is constructed only after that rejection at pipeline/cross_ontology_rewrite_variants.py:1324-1495.

Impact

The required rewrite fit rows cannot be produced with the existing public variant constructor.

Required repair

Implement and audit a fit-safe rewrite presentation constructor for exactly the three permitted fit presentations, or generalize the builder while keeping score-only twins/challenges inaccessible to fitting.

8. Score presentation allocation is not specified

Evidence

The all_axes stratum “additionally uses” four score-only presentations at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:136-141.
The exact stratum counts are stated at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:154-165, but no count is allocated to each presentation and no rule says whether presentations are separate or composed with renderer, theory, and depth axes.
Existing Horn variant kinds and expectations are separate cases at pipeline/cross_ontology_horn_variants.py:31-97.
Resource pair directives are separate cases at pipeline/cross_ontology_resource_variants.py:61-87 and pipeline/cross_ontology_resource_variants.py:772-868.
Rewrite variants are likewise emitted as distinct cases at pipeline/cross_ontology_rewrite_variants.py:1324-1495.

Impact

There is no deterministic way to fill the 96 all_axes rectangles, pair twins to bases, allocate invariant versus changed-answer cases, or decide legal renderer/presentation composition.

Required repair

Freeze a split-by-stratum factor table with exact quotas summing to every published count. For each cell specify theory pool, depth, renderer, presentation, base-pair identity, expected disposition, answer derivation, and allowed compositions.

9. Query semantics and paraphrases are not generative specifications

Evidence

The preregistration requires two semantic queries and two paraphrases per semantic rectangle at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:117-121, but provides no query grammar, templates, evaluator, or selection rule.
The existing factorial board has only two fixed SemanticProbe classes at pipeline/ettr_factorial_qualification_board.py:99-104, a fixed evaluator at pipeline/ettr_factorial_qualification_board.py:504-526, hand-selected definitions at pipeline/ettr_factorial_qualification_board.py:529-573, and two fixed query byte forms at pipeline/ettr_factorial_qualification_board.py:407-433.

Impact

Those probes do not generate valid contrastive queries for arbitrary theories, worlds, commands, and depths. Query choice would become an implementer degree of freedom.

Required repair

Freeze per-ontology query candidate grammars, exact and independent evaluators, the two paraphrase encodings, answer vocabulary, and SHA-ranked selection after the finalized edge-contrast test.

10. Target balancing and ABSTAIN semantics are undefined

Evidence

The preregistration requires exact 50/50 target balance per ontology/stratum/query/paraphrase while balancing ABSTAIN separately at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:289-304.
Factorial probe targets are Boolean at pipeline/ettr_factorial_qualification_board.py:108-123 and pipeline/ettr_factorial_qualification_board.py:504-526.
Matrix rows instead carry directives and terminal expectations at pipeline/cross_ontology_qualification_matrix.py:64-79 and pipeline/cross_ontology_qualification_matrix.py:201-315.
Resource variant cases carry disposition directives and full outcomes at pipeline/cross_ontology_resource_variants.py:193-203 and pipeline/cross_ontology_resource_variants.py:806-865.
Rewrite uses a structured VariantOracle at pipeline/cross_ontology_rewrite_variants.py:219-228.

Impact

There is no canonical projection from structured terminal outcomes to the balanced query label, nor a denominator for 50/50 strata containing ABSTAIN or REJECT.

Required repair

Define the complete label alphabet and projection from each oracle outcome. Publish an exact balance table per answer class, state whether dispositions are excluded from binary balance, and freeze deterministic query selection when a cell cannot meet the requested label.

11. No materializer maps ontology cases to ETTR continuation targets

Evidence

ETTRContinuationBatch requires dataset/manifest commitments, episodes, initial and terminal packet targets, causal rectangles, transaction targets, and disposition flags at train/ettr_data_contract.py:1004-1018; validation replays and checks the batch at train/ettr_data_contract.py:876-1136.
Equivariance training additionally requires slot, type, relation, and value permutations and masks at train/ettr_objectives.py:567-650.
Existing qualification matrix rows store hashes, directives, and expectations, not ETTR packet/transaction tensors, at pipeline/cross_ontology_qualification_matrix.py:64-79.
The concurrent fail-closed freeze gate can audit a future canonical JSONL (pipeline/freeze_ettr_isolated_learnability.py:601-634) but its materialize command explicitly reports that no admitted production row generator exists (pipeline/freeze_ettr_isolated_learnability.py:1065-1077).

Impact

Even after selecting semantic cases, there is no canonical CPU path that emits the tensors consumed by the preregistered arms. Packet slots, transaction steps, dispositions, query-read positions, and alignment permutations would all be invented during implementation.

Required repair

Implement a versioned CPU materializer that maps each ontology terminal state to ETTRPacketTargets, each operation to complete ETTRTransactionTargets, each query to token targets/read indices, and each structural variant to ETTRVariantAlignment. Require independent oracle replay and ETTRContinuationBatch validation before hashing artifacts.

12. The binding-deranged control contradicts the anti-leakage donor gate

Evidence

Arm 3 reassociates supervision within the same ontology/depth/renderer/answer stratum at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:260-273.
The anti-leakage gate requires every wrong-WORLD, wrong-COMMAND, and shuffled-state donor to change the assessor target at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:297-301.

Impact

Reassociation within the same answer stratum preserves the answer by construction, while the gate requires the donor to change it. No exact derangement or component-level interpretation resolves the contradiction.

Required repair

State which target components must be preserved and which must change. Remove answer from the donor stratum if the query target must change, or redefine the gate as a packet/transaction-binding test with an unchanged query label. Freeze a total seeded derangement algorithm and its no-fixed-point checks.

13. Confirmation encryption and open-once custody are not implementable

Evidence

The preregistration requires encrypted immutable confirmation artifacts and a root-signed manifest at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:205-212.
It requires exactly one authorized confirmation opening at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:308-321.
Existing authority code signs factorial-board/execution commitments in train/ettr_factorial_authority.py:115-218; it does not define this dataset's encryption, key custody, or open-once state machine.

Impact

No encryption algorithm, key authority, nonce/AAD derivation, ciphertext schema, signature schema, or access ledger is specified. Secure randomized encryption also cannot have a predetermined ciphertext hash unless its randomness is frozen or the post-encryption artifact is separately committed.

Required repair

Freeze the dataset-manifest and signature schemas, authority public key, authenticated-encryption algorithm, key custodian, nonce/AAD policy, and append-only opening receipt. Distinguish deterministic semantic plaintext generation from custodian-generated ciphertext, then hash and sign the latter after encryption.

Additional Determinism and Feasibility Defects

14. Zero command overlap may be combinatorially impossible at resource depth 1

Evidence

Zero command overlap across train/development/confirmation is required at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:289-296.
A rectangle needs two commands at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:108-116.
The resource command alphabet has only three operator symbols at pipeline/cross_ontology_resource_board.py:175-180.

Impact

If “command overlap” means semantic operation sequence and more than one split contains depth-1 resource rectangles, each split needs at least two commands from a universe of three. Even train versus one score split cannot be disjoint. The preregistration also does not assign depths to each score stratum, so feasibility cannot be decided.

Required repair

Define command identity precisely: semantic AST, rendered bytes, or world-bound instance. Publish the complete split/stratum/depth table and a pre-materialization cardinality proof. If semantic identity is intended, expand the command grammar or relax the overlap gate under a new commitment.

15. Leakage and overlap gates have no canonical algorithms

Evidence

The preregistration requires semantic-world, theory, command, opaque-name, graph-isomorphism, token-sequence, normalized 13-gram, and metadata-classifier gates at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:289-304.
It does not define text normalization, tokenizer/version, graph canonical labeling, opaque-name extraction, pairwise split scope, classifier features, solver, hyperparameters, seed, folds, or the meaning of chance for the classifier threshold.

Impact

Gate outcomes are implementation-dependent and therefore cannot certify a deterministically frozen dataset.

Required repair

Freeze every fingerprint function and comparison scope. Pin normalization and tokenizer hashes, graph canonicalization, classifier implementation/version, features, solver, seed, train/test folds, confidence rule, and multiclass chance calculation.

16. Frozen source labels are path-ambiguous and current HEAD has drifted

Evidence

The preregistration pins commit 854d3d4... and source hashes at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:31-51.
The published “Qualification source” hash corresponds to train/ettr_qualification.py, but the path is not stated.
The current supervisor source differs from the preregistered hash; the file at the pinned commit matches it.

Impact

The commitment is recoverable only if the implementer guesses the intended paths and builds from the detached frozen commit rather than the current checkout.

Required repair

Add a canonical source inventory of {path, sha256, commit} and require a clean detached checkout of the pinned commit for source-frozen construction. Any materializer added after the preregistration needs its own protocol version and source commitment.

The untracked freeze gate that appeared during this audit improves failure handling but is not a preregistered source repair: it records several of the same unresolved clauses at pipeline/freeze_ettr_isolated_learnability.py:806-921.

Verified Foundations

The following parts are not blockers:

The master commitment at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:170-179 reproduces from its stated literal preimage.
The existing matrix, factorial, and hybrid score-board payload hashes at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:214-223 reproduce.
The frozen Horn, rewrite, and resource fit/score theory-index pools at R12_ETTR_ISOLATED_LEARNABILITY_PREREG.md:86-95 are valid, internally unique by behavior in the current generators, and behaviorally disjoint between fit and score pools.
Existing ETTR batch validation is strict enough to serve as a downstream materialization gate once the missing mapping and rectangle semantics are frozen.

Minimum Repair Order

Freeze the canonical split schema, candidate tuple, axis/quota table, query grammar, and exact command identity.
Resolve command depth semantics and the resource depth-1 overlap cardinality.
Reconcile 16-row semantic rectangles with four-row ETTRCausalRectangle objects and freeze the update/repetition schedule.
Implement the shared typed AST/renderers and fit-safe rewrite presentations.
Define outcome projection, ABSTAIN balancing, all score-presentation allocation, and the binding-control derangement.
Implement and independently validate the ontology-to-ETTR CPU materializer.
Freeze overlap algorithms and external confirmation custody.
Produce a dry-run cardinality/feasibility report before writing any claim-bearing train, development, or confirmation artifact.

Until all eight repairs are committed under a new explicit protocol version, CPU materialization must remain NO-GO.