results: confirm C2 feedback amortization bottleneck

1 files changed, 10 insertions, 5 deletions

diff --git a/NOVELTY.md b/NOVELTY.md
index 3755595..c044927 100644
--- a/NOVELTY.md
+++ b/NOVELTY.md
@@ -76,11 +76,16 @@ identifies the traffic relationship without observing the teaching component.
 
 - The inherited learned-feedback backbone preserves performance with depth better than fixed DFA
   in the audited flattened-CIFAR MLP setting.
-- Controlled pilots show that per-cell residualization can protect learning from soma-coupled and
-  endogenous top-down traffic; the latter remains a validation-only, single-seed result until C1 is
-  completed.
-- Simultaneous batched perturbations make the inherited calibration practical in this codebase;
-  a hardware-independent query/FLOP advantage is not yet established.
+- Frozen controls show that per-cell residualization protects learning from soma-coupled traffic.
+  It mitigates but does not fully remove endogenous top-down traffic, so arbitrary contextual
+  innovation is not an allowed teaching-signal claim.
+- Simultaneous batched perturbations have a frozen hardware-independent advantage: K1/every4
+  retains 112.9% of the K16/every4 gain over DFA with 16x fewer logical loss queries, 11x less
+  calibration work, and 5.3x less total forward-equivalent work on CIFAR-10 d20/w64.
+- Direct node perturbation solves the frozen useful-depth task while the amortized context
+  vectorizer does not. This identifies feedback amortization as the current engineering
+  bottleneck; it is not a novelty claim and the direct estimator's 68.4x work precludes presenting
+  it as the scalable algorithm.
 
 ## Claims currently forbidden