results: close Oral-A v3 causal-capture gate

1 files changed, 24 insertions, 0 deletions

diff --git a/RESULTS.md b/RESULTS.md
index 50377ba..9a6fa81 100644
--- a/RESULTS.md
+++ b/RESULTS.md
@@ -683,6 +683,30 @@ post-failure oracle diagnostics, not trainable-method results. They rule out a
 naive basis expansion and point toward both better causal sample efficiency
 and a more informative hierarchical/high-level feedback context.
 
+V3 tests whether the remaining regression gap comes specifically from
+estimating per-example coefficients before fitting A/G. It perturbs random A/G
+matrices directly, so each induced hidden intervention already contains the
+output-error context and the antithetic scalar estimates the exact matrix
+statistic needed by the vectorizer delta rule. Mechanics are strong: at batch
+128 the frozen synthetic one-query MSE is `0.03381x` the coefficient estimator,
+and exact no-BN/BN JVP errors are below `2e-10`.
+
+That gain does not transfer to early ResNet credit. All four frozen-forward
+records are finite and the selected rate is again `eta_A=0.01`:
+
+| estimator | early-third alignment | all-layer alignment |
+|:--|--:|--:|
+| channel-subspace V2 reference | 0.007209 | 0.052740 |
+| vectorizer-subspace V3 | 0.007139 | 0.062579 |
+
+The common all-layer endpoint improves, but the early endpoint is unchanged
+and misses three frozen advancement checks. Higher rates are worse. Thus the
+coefficient-regression stage was not the dominant early-layer limitation under
+the real causal signal. V3-2 is not launched. The result redirects development
+toward informative hierarchical/high-level feedback context or a mechanism
+that addresses remaining cross-layer/parameter-space noise; it does not
+justify another rate or warmup sweep.
+
 ## How to run
 `experiments/run.py --mode {bp,fa,dfa,sdil} --dataset {mnist,fmnist,cifar10} --depth D --residual {0,1} --act {tanh,gelu,silu,relu}`
 Batteries: `experiments/run_v2.sh <ds> "<depths>" <res> <act> "<seeds>" <ep> <pfx>`.