analysis: diagnose Oral-A calibration failure

1 files changed, 12 insertions, 1 deletions

diff --git a/RESULTS.md b/RESULTS.md
index 6b11b34..e14cec3 100644
--- a/RESULTS.md
+++ b/RESULTS.md
@@ -623,7 +623,7 @@ The full 200-epoch A3 gate failed:
 | SDIL | 10.00 | no | NaN | 9.165e14 |
 
 SDIL reached `35.26%` at epoch 20, fell to `22.82%` at epoch 80, and became
-nonfinite at epoch 90. It passed only the BP-reference and MAC checks; it failed
+nonfinite at epoch 89. It passed only the BP-reference and MAC checks; it failed
 the within-5-point, DFA-advantage, alignment, and all-finite checks. The failure
 is specifically for the frozen recipe selected under the short cosine screen
 and transferred to the long step schedule. It is not evidence that every
@@ -631,6 +631,17 @@ possible SDIL optimizer must diverge, but it does falsify the preregistered
 standard-ResNet scaling claim. A4 was not opened and confirmation seeds 10--14
 were not touched.
 
+The executable post-failure diagnosis finds a specific precursor rather than
+only a bad endpoint. Before nonfiniteness, the apical prediction--target cosine
+never exceeds `8.51e-5` in magnitude, while calibration MSE differs from target
+power by at most `6.96e-8` relatively. Target power grows `2560.7x` from epoch
+1 to 80 and `2.13e9x` by epoch 87. Thus the positive short-run teaching
+alignment cannot be attributed to successful causal calibration of `A`; the
+full-spatial K1 estimator is effectively all noise after projection into the
+small channel-gated vectorizer. This is a post-failure diagnosis, not a passed
+preregistered result, and motivates a separately labelled representable-
+subspace estimator rather than a threshold change to Oral-A v1.
+
 ## 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>`.