R12 CDRL Neural Optimization Preregistration

Status: AUTHORIZED NEURAL OPTIMIZATION BOARD ONLY. This is not a reasoning, workspace, Shohin-adapter, language-bridge, or primitive-novelty claim. It tests Conjecture C from R12_CONFLICT_DRIVEN_RESIDUAL_LOCALIZATION.md on a fixed tiny updater class with matched resources.

Protocol: R12-CDRL-NEURAL-v1

Cluster: Newton H100 (normal, one GPU). Isolated output under artifacts/r12/cdrl_neural_v1/. Must not write flagship, ACW, or shared SFT paths.

1. Frozen claim

At equal parameters, labels, and optimizer updates, training a GRU residual predictor on Nerode cores (core) exceeds each of full, rand, and hard on depth-OOD exact state accuracy by at least +5.0 percentage points in the median over three locked seeds.

Failing any control by that margin is a reject. A tie or win only over full is a reject.

2. Family and data

Heisenberg mod M=5 with identity padding P (same algebra as the CPU mechanics suite). Train histories: length 8..16 inclusive, formed by placing 1..4 essential events from {A,B,C} and filling the rest with P. Held-out depth-OOD: length 20..28 with the same essential-count band. Fit-IID eval: held-out length 8..16 with disjoint RNG stream.

Seeds: 2026071601, 2026071602, 2026071603.

Labels per arm: 12,288. Updates: 2,400. Batch size: 256.

3. Arms (matched)

Arm	Training histories
`full`	raw padded histories
`core`	lex-min residual-preserving cores
`rand`	random subsequence of length `\|core\|` (same indices RNG per example id)
`hard`	raw histories; after update 800, replace the next 1,600 updates' sampling
distribution by the top-quartile CE examples from a frozen probe pass

All arms share identical GRU width (h=64), embedding (d=32), parameter count, optimizer (AdamW lr 1e-3, wd 0.01), and loss (sum of three coordinate CE heads).

4. Metrics and gates

Primary: depth-OOD exact state accuracy (x,y,z all correct). Secondary (reported, not gated): fit-IID exact accuracy; mean coordinate accuracy.

Promotion (advance=true) only if for the median seed:

acc_core - acc_full  >= 0.05
acc_core - acc_rand  >= 0.05
acc_core - acc_hard  >= 0.05

Otherwise advance=false. No threshold shopping after scores are read.

5. Explicit non-claims

Not Shohin reasoning, SFT, or base-model improvement
Not ACW Track S/C
Not a new state ontology
Not authorization to scale to language

6. Artifact layout

artifacts/r12/cdrl_neural_v1/
  prereg_sha256.txt
  seed_{SEED}/
    arm_{ARM}/
      model.pt
      train_receipt.json
    eval.json
  decision.json

One attempt per seed/arm output path; refuse overwrite.