# Oral-A recovery v2: BCI-v2-authorized standard-depth scaling ## Status and provenance boundary This is a new confirmation branch opened only by the complete calibrated oral-B-v2 pass. It does not reopen or relabel the failed learned-vectorizer Oral-A-v1--v4 branches, and it does not alter the closed legacy recovery whose prerequisite was the failed original oral-B R2 gate. The experiment and every numerical threshold below are copied verbatim from `ORAL_A_RECOVERY.md`, which was committed before any standard-depth endpoint was generated. The only protocol change is the prerequisite: the new branch requires both the complete D4 accept pass and `oral_b_v2_calibrated_recovery_confirmation_v1`. No recovery-v2 test endpoint may be generated until this document, its runner, analyzer, and smoke audit are committed together in a clean tracked revision. This separation matters for interpretation. The calibrated BCI-v2 experiment establishes that role-vectorized somato-dendritic innovation can carry local TD/outcome surprise without Kolen--Pollack reciprocity. The panel below then tests the complementary engineering claim that the already established dynamic-innovation/reciprocal substrate retains performance and alignment as a canonical image network becomes deeper. Neither result alone is presented as proving the other. ## Fixed panel and reuse boundary Use CIFAR-10 ResNet-20/32/56 with width 16, BatchNorm, option-A shortcuts, batch size 128, all 50,000 training examples, 200 epochs, SGD momentum 0.9, weight decay `1e-4`, base learning rate 0.1 with 10-fold drops at epochs 100 and 150, no warmup, and model/data-loader seeds 10--14. Test is evaluated exactly once at the endpoint; validation and intermediate test evaluations are zero. The matched methods are: 1. exact BP on the identical forward architecture; 2. tuned DFA at its already selected hidden rate 0.03 and output rate 0.1; 3. clean reciprocal Kolen--Pollack at hidden/output rate 0.1; and 4. dynamic innovation on the same reciprocal substrate, with traffic ratio 4, traffic seed `5000 + model_seed`, 64 instruction-off calibration examples, one closed-form neutral projection, and no later predictor update. The already frozen D4 clean-KP and dynamic records at ResNet-20/seeds 10--14 are reused verbatim rather than rerun. Recovery v2 therefore adds exactly 50 records: BP and DFA at depth 20, and all four methods at depths 32 and 56. Together with D4 this forms an exact 60-cell panel. All new records must share one clean tracked source revision; all D4 records retain their separate frozen source revision. No completed record may be deleted, replaced, or pooled with a pilot. Fixed HFA remains closed after its preregistered short gate failed. FF, PEPITA, canonical EP, BurstCCN, and Dual Prop retain their method-native audits and are reported as separate baselines rather than silently moved onto this matched standard-ResNet grid. ## Frozen mechanism and cost invariants Every dynamic record must retain all D4 invariants: finite 200-epoch trajectory; mean early-third credit alignment measured only diagnostically; final feedback/forward cosine at least 0.98 and epoch-151--200 mean at least 0.97; instruction-to-teaching RMS error at most `1e-4`; maximum post-projection traffic ratio and absolute soma slope at most `1e-5`; zero instruction leakage into neutral observations; exactly 64 predictor-update examples; exactly one neutral observation per ordinary example; and zero task-loss queries. At every depth, dynamic and clean KP must each use at most `1.34x` the matched BP MAC estimate. Dynamic elementwise projection work is reported separately and must be positive. Peak allocated memory may not exceed 8 GiB on the authorized GTX 1080 devices. Wall time is reported but is never substituted for MACs, queries, or memory. Every record must identify an NVIDIA GTX 1080 and visibility restricted to authorized timan107 physical GPU 5 or 7. ## Frozen oral-A gate The five model/data seeds are the independent paired units. One-sided 95% Student-t bounds use four degrees of freedom. Recovery v2 passes only if every record and every audited value is finite and all of the following hold: 1. Mean BP accuracy is at least 90% at every depth and every dynamic endpoint is at least 87%. 2. At each depth, mean dynamic accuracy is within 2 points of matched BP and the one-sided 95% upper bound on the paired deficit is at most 3 points. 3. At each depth, mean dynamic accuracy is within 1.5 points of clean KP and the upper bound on that paired deficit is at most 2.5 points. 4. At depth 56, dynamic exceeds tuned DFA by at least 2 points on average and the one-sided lower bound on the paired advantage is at least 1 point. 5. Dynamic gains at least 0.5 points from depth 20 to 56 on average, its one-sided lower bound is nonnegative, and at least four of five paired seeds improve. Its mean depth gain must also be no more than 1 point below BP's paired depth gain. 6. Mean dynamic early-third alignment is at least 0.85 at every depth; every depth-56 seed is at least 0.80; and the depth-56 mean retains at least 90% of the depth-20 mean. 7. Every mechanism, query, MAC, elementwise-work, memory, source, split, and evaluation invariant above passes without exception. The executable runner and immutable complete-grid analyzer are `experiments/oral_a_dynamic_scaling_v2.py` and `experiments/analyze_oral_a_dynamic_scaling_v2.py`. A complete pass raises the formal milestone from 8 to 9 and establishes the standard-depth oral-A claim. Any failure is retained, leaves the score at 8, and closes this branch without depth, seed, optimizer, or threshold repair.