`Pskr.Recalibrator.run/0` reads `pskr_calibration_samples`, bins
each sample per (band × feature), and writes spot-density stats to
`pskr_feature_bins` so an operator can read whether a feature
actually discriminates propagation at the threshold granularity
the scorer uses.
Bins, not regression: `BandConfig` already encodes scoring as
discrete thresholds, so the bin output matches that shape and an
operator can copy adjusted thresholds directly without translating
from regression coefficients.
Self-healing: corpus too thin ⇒ run row written with status
`skipped_insufficient_data` and the analysis is a no-op until next
fire. `min_total_samples = 1000` (≈ 4-5 days of CONUS PSKR
activity); per-band threshold is 100. Both surface in the run row's
`notes`.
Auto-applies nothing. Weight changes still go through human review
of `BandConfig.@band_configs` and a code commit. The recalibrator
is a read-only analyst that stays out of the production scoring
path.
Features binned (matching the scorer's discriminating fields):
* pwat_mm — humidity U-shape candidate
* hpbl_m — boundary layer (mechanism vs scoring re-eval)
* min_refractivity_gradient — refractivity threshold validation
* surface_pressure_mb — pressure-front proxy
* kp_index — aurora boost magnitude tuning
Schema: two tables.
* `pskr_recalibration_runs` — one row per fire with corpus
stats, status, notes
* `pskr_feature_bins` — one row per (run, band, feature, bin)
with sample_count, spot_count_total/avg/p50/p90
Cron: `0 4 * * 0` (Sundays 04:00 UTC, off-peak, post-climatology).
Manual reruns enqueue with no args.
Tests cover the empty-corpus skip path, sub-threshold totals,
per-band threshold gating, the actual bin emission, nil-feature
handling, spot-count averaging, and the always-records-a-run
audit invariant. 8 new tests, 3282 total passing.
Backfill pipeline untouched.
