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Jungfraujoch/process
leonarski_fandClaude Opus 4.8 107bcae0f0
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merge: de-bias the error-model variance fit (chi^2 was ~2.2, now ~1) and report chi^2
RefineErrorModel fits the variance model a*sigma^2 + (b*<I>)^2 to the binned
*median* of the squared symmetry-mate deviations, chosen for robustness. But a
single deviation squared over its variance is chi-square(1)-distributed, whose
median is only 0.4549 of its mean, so the fit was calibrating the variances to
0.4549x their true value: the merged sigmas came out ~1.48x too small and the
achieved reduced chi^2 was 1/0.4549 = 2.2, not 1. The error model was internally
well-behaved (flat chi^2 across resolution) but globally over-confident, which
inflated ISa (=1/b) by ~1.48x and made the exported sigmas too optimistic for
downstream weighting / French-Wilson.

Divide the binned median by the chi-square(1) median (0.4549) to recover an
unbiased estimate of the mean E[dev^2]=sigma^2, keeping the robustness of the
median while targeting reduced chi^2 = 1. Also compute the achieved median
reduced chi^2 (same normalization) and report it on the "Error model" line so
mis-calibration can no longer drift silently.

Verified: HEWL rotation a 0.588->1.292, b 0.052->0.077, ISa 19.1->12.9, chi^2
2.17->1.06; serial Jet8 ISa 1.0->0.7, chi^2 0.92. Relative ISa comparisons and
all CC1/2/CCref/anomalous metrics are unchanged (sigma-independent or a common
constant); only the absolute sigma calibration is corrected.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-28 15:57:42 +02:00
..
2026-06-23 20:29:49 +02:00
2026-06-23 20:29:49 +02:00