# R12 PCFT Adversarial Audit **Decision:** NO-GO for a neural PCFT preregistration from the v1 scorer pass. The v1 algebra and exhaustive counts survive; the claimed transport interface does not. ## 1. What survives For uniform `x in F_17^4`, a complete packet answers every late linear functional exactly. A packet containing only `(x_0,x_1)` answers all consumers whose effective functional lies in `span(e_0,e_1)`, and has exact accuracy `1/17` whenever the effective functional has a nonzero hidden component. A bijection of the 17 answer symbols preserves those accuracy counts. The collision theorem and the 15-cell exhaustive result are correct. This establishes only that a full vector contains information absent from a rank-two projection. ## 2. Claim-blocking defects 1. **No packet transport occurs.** V1 composes all future affine events into a single effective functional and applies that functional to the initial packet. It never invokes a shared updater on `(packet,event)` after source deletion, so it does not test the mechanism PCFT needs. 2. **Custody is simulated rather than process-enforced.** Phase one freezes packet hashes, but the scorer later re-enumerates sources in the same process. Pure packet readers now have no source argument, yet this remains a code convention rather than a separate-process boundary. 3. **Scorer-side recoding is not a late-interface test.** Comparing `pi(prediction)` with `pi(truth)` is exactly equivalent to comparing raw values when `pi` is bijective. A candidate must instead receive the fresh codebook and emit the recoded symbol itself. 4. **The rank-two motor is favorable only on the public subspace, not information-matched.** Both arms have four fields, but the motor uses only 289 distinct packets versus the state's 83,521. Padding equalizes tuple width, not retained entropy. It is a useful negative control, not the decisive neural comparator. 5. **Sixty-four random fingerprints almost surely reveal the complete state.** In four dimensions over `F_17`, an overcomplete random linear system is full-rank with overwhelming probability. PCFT is therefore state distillation through random projections unless a stronger resource result is demonstrated. Beating only the rank-two motor would show that richer supervision carries more information. 6. **Unseen depth is not unseen scale.** A fixed `F_17^4` board remains compatible with finite source tables. A defensible uniformity claim must freeze tests across unseen source states, event parameters, renderings, compositions, state dimensions, and depths with one variable-size model. 7. **The exact affine solver is an oracle reference, not a control PCFT can beat.** A tie at ceiling defines the remaining oracle gap. Decisive controls are same-information direct-state and fixed-full-rank supervision under the same architecture and resource ledger. The original v1 horizon flag was also tautological. It was repaired before the canonical artifact was frozen: the current implementation executes a source-free horizon-triggered reader over all 15 decisive cells and all 83,521 sources, scoring exact through depth 8 and zero at depth 9. This repair does not resolve the seven transport/custody defects above. ## 3. Required v2 boundary Before any neural fit, an exact v2 must provide: 1. separate oracle, writer, stateless one-event updater, and fresh reader processes; 2. serialized packet handoffs and packet hashes committed before challenge generation; 3. no source, source pointer, event history, verifier, or stale packet channel in updater/reader interfaces; 4. independent late output permutations consumed by the reader, with the reader emitting the recoded symbol; 5. executed source-visible, source-pointer, query-visible, stale-packet, event-history, shuffled-packet, and horizon decoys; 6. direct-versus-incremental state agreement and donor packet swaps; 7. exact ledgers for utilized packet entropy, persistent state, labels and independent label rank, parameters, examples, updates, FLOPs, and search budget; 8. score-blind confirmation generated only after checkpoint commitment. The v2 exact process gate may validate custody and transport mechanics. It still cannot establish learned reasoning. ## 4. Prior-art boundary Random linear fingerprints are universal hashing and linear sketches. Learned future-prediction representations overlap predictive-state representations, successor features, and random action-conditional prediction objectives. Explicit recurrent state and state reification are established. The only potentially defensible project contribution is the combined, process-enforced, finite-precision, post-commit training and evaluation protocol. No world-first claim is authorized without a broader primary-literature review. Starting primary sources: - universal hashing: https://www.cs.princeton.edu/courses/archive/fall09/cos521/Handouts/universalclasses.pdf - predictive state representations: https://papers.neurips.cc/paper/1983-predictive-representations-of-state.pdf - successor features: https://papers.nips.cc/paper_files/paper/2017/hash/350db081a661525235354dd3e19b8c05-Abstract.html - random action-conditional predictions: https://proceedings.neurips.cc/paper_files/paper/2021/hash/c71df24045cfddab4a963d3ac9bdc9a3-Abstract.html - linear streaming sketches: https://theory.stanford.edu/~matias/papers/ams_stoc.pdf - state reification: https://proceedings.mlr.press/v97/lamb19a.html ## 5. Shohin decision Preserve the v1 result as a static positive/control theorem. Do not train a PCFT neural model from it. Implement only the separately preregistered exact v2 transport/custody harness. No Shohin adapter, SFT, or H100 job is authorized.