leonarski_fandClaude Opus 4.8
a47b376dc3
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At the jet's ~1000x multiplicity R-free is bias-limited, and the merge had NO outlier rejection - serial data zingers/overlaps/mis-indexed frames bias every merged mean. Add a robust per-observation cut: drop observations whose corrected intensity lies > reject_nsigma error-model sigmas from the reflection's MEDIAN. The error-model sigma already captures the genuine (partiality) scatter, and the median is a robust centre, so only the tail beyond the real spread is removed - not good partials. The median is computed in RefineErrorModel (which already pools the observations per reflection); AddImage applies the cut. Env-gated via PR_REJECT=<nsigma> (off by default); logs the count removed. On the jet (CC proxy) it lifts CCref +8 (nsigma 6, 0.6% cut) to +11 (nsigma 3, 7.4% cut) - the cut is vs the data's own median, not the reference, so the gain is real cleaner means. R-free validation + the nsigma sweet spot (over-rejection risk at low nsigma) are for Filip's full-jet R-free. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>