Ran recalibrate_algo.py against the full local prop_dev (81,994 contacts,
18.6M HRRR rows) and derived per-band composite weights for the nine
bands with >=200 matched contacts. Moisture (dewpoint/PWAT/surface N)
is consistently beneficial through 5.76 GHz, reverses at 24 GHz; rain
scales sqrt(rain_k) not linearly so 24 GHz gets 0.215 rain weight
instead of the linear-ratio 0.95. 10 GHz stays as the reference band
(defaults); 47+ GHz inherits defaults (n<200).
- BandConfig.weights/1 returns per-band override or default fallback
- @band_configs carries :weights on 222/432/902/1296/2304/3400/5760/24G
- Recalibrator.compute_factors/3 + fit(band_mhz:) band-aware fitting
- Scorer + ContactLive.Show pass band_config to weights/1
- algo.md Part 2d documents the 2026-04-18 analysis + derivation rule
- scripts/derive_band_weights.py turns correlations into weight maps
- report preserved at docs/algo-reports/2026-04-18-recalibration.md
