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Daniel Rosel
2026-04-08 17:42:51 +02:00
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paper/src/chapters/04-results.tex
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@@ -92,19 +92,7 @@ In our complete training runs we logged $\approx 180$ days of net compute time.
\label{fig:final_focus_coi_preservation_grid} \label{fig:final_focus_coi_preservation_grid}
\end{figure} \end{figure}
\begin{figure}[ht]
\centering
\input{chapters/figures/results/includes/final_focus_revenue_delta.tex}
\caption{Defended-minus-baseline revenue delta over contamination for the final cohort. The strongest high-contamination deviation begins at $\alpha=0.7$, followed by recovery toward near parity by $\alpha=1.0$.}
\label{fig:final_focus_revenue_delta}
\end{figure}
\begin{figure}[ht]
\centering
\input{chapters/figures/results/includes/final_focus_risk_deltas.tex}
\caption{Defended-minus-baseline leakage and volatility deltas for the final cohort. Leakage remains lower for the defended policy across the full contamination range.}
\label{fig:final_focus_risk_deltas}
\end{figure}
\subsection{Interpretation and Insights} \subsection{Interpretation and Insights}
The Mann-Whitney result ($p<0.001$) confirms that per-session divergence gaps distinguish the two actor classes with near-zero overlap in rank ordering. This is the condition required for distinguishability to act as a useful control signal in the pricing loop rather than just an auxiliary classifier score. The Mann-Whitney result ($p<0.001$) confirms that per-session divergence gaps distinguish the two actor classes with near-zero overlap in rank ordering. This is the condition required for distinguishability to act as a useful control signal in the pricing loop rather than just an auxiliary classifier score.