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+INPUT ../runs/ctt_base_context_obs_learned_dominance_train_to_test/table.tex
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+INPUT ../runs/ctt_base_context_obs_nonlinear_dominance_basic_positive_train_to_test/table.tex
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workspace/latex/main.tex

@@ -59,7 +59,7 @@ test success at 25.69\% coverage. We keep the metric boundary explicit:
 \outcomeptr{} is reported only after generated candidates are rolled out, while
 distance-only support diagnostics are \pptc{}. These runs are therefore
 diagnostic evidence for the Atlas thesis and the next selector/generator gate,
-not an unqualified SOTA claim.
+not a final deployment claim.
 \end{abstract}
 
 \section{Introduction}
@@ -611,6 +611,27 @@ success selector gap. The paper should therefore treat train-only dominance as
 evidence that the current selector is underpowered, not as a solved deployment
 method.
 
+\begin{table}[t]
+\centering
+\caption{Nonlinear train-calibrated selector diagnostic. The model and
+threshold are selected only on held-out train-calibration rows, then evaluated
+once on the held-out test rollout rows. The best nonlinear row does not beat
+Table~\ref{tab:ctt-base-context-obs-learned-train-dominance}, so the current
+bottleneck is not just linear separability in the dominance selector.}
+\label{tab:ctt-base-context-obs-nonlinear-train-dominance}
+\scriptsize
+\resizebox{\linewidth}{!}{\input{../runs/ctt_base_context_obs_nonlinear_dominance_basic_positive_train_to_test/table.tex}}
+\end{table}
+
+Table~\ref{tab:ctt-base-context-obs-nonlinear-train-dominance} tests the
+obvious stronger-selector hypothesis with histogram-gradient and random-forest
+diagnostics. The best nonlinear train-calibrated row reaches 30.56\% selected
+test success, below the 31.25\% clean ridge row above, while using the same
+test proposal set and leakage-audited train calibration source exclusion. This
+negative result supports the next engineering target: richer visual-language or
+object-centric chart features and outcome-vector utility modeling, not merely a
+more flexible shallow selector over the current feature set.
+
 \section{Reproducibility Artifacts}
 
 The current draft is backed by explicit artifacts:
@@ -648,10 +669,13 @@ The current draft is backed by explicit artifacts:
   measured rows; it can use rollout row scores or recompute scores from a
   train-only utility-energy checkpoint.
   \item \texttt{scripts/eval\_learned\_dominance\_selector.py} trains a small
-  validation-calibrated dominance model over deployment-visible candidate
-  features and evaluates it on held-out measured test rows; it also logs
-  feature/target ablations, including context metadata and tangent-code
+  validation- or train-calibrated dominance model over deployment-visible
+  candidate features and evaluates it on held-out measured test rows; it also
+  logs feature/target ablations, including context metadata and tangent-code
   variants, for selector diagnostics.
+  \item \texttt{scripts/eval\_nonlinear\_dominance\_selector.py} runs the
+  train-calibrated nonlinear selector diagnostics in
+  \texttt{runs/ctt\_base\_context\_obs\_nonlinear\_dominance\_*}.
   \item \texttt{scripts/eval\_chart\_positive\_memory\_proxy.py} and
   \texttt{scripts/build\_ctt\_proxy\_comparison.py} generate the local-atlas
   baseline and validation proxy gate table.
@@ -668,7 +692,7 @@ The current draft is backed by explicit artifacts:
 
 \section{Limitations and Next Steps}
 
-This draft is not an unqualified SOTA claim. The current \ctt{} evidence
+This draft is not yet a final deployment method. The current \ctt{} evidence
 includes validation and test measured generated-candidate rollouts, but the
 selected action fails the internal paper gate even when the test proposal oracle
 passes 50\%. The missing method component is calibrated dominance and a better