results: mark amortized calibration gate passed

1 files changed, 19 insertions, 3 deletions

diff --git a/RESULTS.md b/RESULTS.md
index 0bf097e..382fc2d 100644
--- a/RESULTS.md
+++ b/RESULTS.md
@@ -176,13 +176,29 @@ training-only validation split (hash `8328b206...515b`). All eight runs came fro
 | learned NP | 1 | 16 | 36.52 | 220 | 64.0x | 44.0x | -0.175 |
 | learned NP | 2 | 32 | 36.78 | 220 | 64.0x | 52.8x | 0.150 |
 
-`K=1/every=4` is frozen for confirmation: it exceeds the C3 10x-query/90%-retention threshold in
-validation and is the only candidate that improves on the reference endpoint. The ablation also
+`K=1/every=4` was frozen for confirmation: it exceeded the C3 10x-query/90%-retention threshold in
+validation and was the only candidate that improved on the reference endpoint. The ablation also
 separates directions from update frequency: spending the same 880 queries as `K=2/every=8` or
 `K=4/every=16` is worse, so frequent noisy regression targets are more useful than precise sparse
 targets. GTX-1080 wall time remains approximately 15–23 seconds across the grid despite the 11x
 calibration-work change, demonstrating why the Pareto audit needs hardware-independent work in
-addition to wall time. C3 is not declared passed until frozen multi-seed confirmation.
+addition to wall time.
+
+The frozen full-training/test confirmation used five paired seeds at clean revision `6689994`, with
+no intermediate test evaluation or diagnostics:
+
+| method | n | test acc (%) | batch loss queries | total training forward-eq examples | peak allocated (MiB) | wall (s) |
+|:-------|--:|-------------:|-------------------:|-----------------------------------:|---------------------:|---------:|
+| DFA | 5 | 37.106 ± 0.710 | 0 | 250,000 | 739.8 ± 0.0 | 17.5 ± 2.0 |
+| K16/e4 | 5 | 38.490 ± 0.658 | 15,648 | 2,313,952 | 803.5 ± 0.0 | 22.6 ± 4.7 |
+| **K1/e4** | **5** | **38.668 ± 0.589** | **978** | **437,632** | **739.8 ± 0.0** | **20.8 ± 0.8** |
+
+The mean paired gain over DFA is 1.384 points for K16/e4 and 1.562 points for K1/e4, giving
+112.9% retention. The selected protocol reduces logical perturbation queries 16x, calibration
+forward-equivalent work 11x, and total training forward-equivalent work 5.3x. Its peak allocation
+falls to the DFA level. **Gate C3 passes.** Wall time improves only modestly because fixed/data/GPU
+under-utilization costs dominate this small network, so it is reported but not substituted for the
+hardware-independent result.
 
 ## Legacy credit assignment / depth utility
 Per-layer alignment cos(r_l, −∇_{h_l}L), early-third average, CIFAR no-BN residual: