results: audit Dual Prop state-bias screen

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+# Dual Prop state-bias screen
+
+The central result is positive, but the complete pre-registered gate fails.
+
+In the author Dual Prop miniCNN, neuron-specific activity-dependent bias makes
+the raw local update nonfinite in epoch 1 at every tested bias ratio.  The
+innovation rule stays finite for all 20 epochs and remains close to both clean
+Dual Prop and an oracle that subtracts the generated bias exactly.
+
+| Bias / clean teaching RMS | Raw | Innovation | Oracle |
+|---:|---:|---:|---:|
+| 0.25 | 9.40, nonfinite | 71.10 | 70.58 |
+| 1 | 9.40, nonfinite | 70.18 | 69.80 |
+| 4 | 9.40, nonfinite | 68.96 | 69.86 |
+
+Values are final validation accuracy in percent.  Clean Dual Prop is 69.66%.
+The largest innovation-to-clean gap is 1.44 points and the largest
+innovation-to-oracle gap is 0.90 points.  The maximum bias remaining after
+subtraction is `8.96e-8` of the raw bias, and the predictor sees zero task
+instruction observations.
+
+The complete B1 gate is `fail` for two reasons unrelated to the recovery
+comparison: clean ends 0.34 points below the frozen 70% threshold, and the
+common-bias endpoint differs from clean by 2.28 points even though its teaching
+difference error is exactly zero.  The latter shows that a 0.2-point single-run
+accuracy tolerance is not a reliable identity check on these GPU kernels.
+Because the complete gate fails, B2 is not opened automatically.  A new
+confirmation protocol must be frozen before running more seeds.