dtourolle 13437e0d8b docs: correct scene-boundary detector F1 numbers to measured values ...

The boundary-detection paragraph understated the detector. Replace the stale
"~34% F1 vs ~27%" (a pre-C++-retrain figure with no backing artifact) with the
measured numbers at the shipped ±20s tolerance:
  - leave-one-out macro boundary F1 = 44.1% (honest generalisation)
  - grayscale baseline               = 29.8%
  - train-all (shipped model)        = 72.9% (per-film 51-86%)
computed from experiments/results/scene_boundary/xgb_report.json and per-film
leave-one-out runs of train_xgb_cpp.py. Also correct the false claim that the
low-contrast grades "cannot generalise held out" — Scarface held out scores 32%,
Café Society 51%, both above grayscale (0% and 31%).

Split the evolution figure into two panels so the strict-±2s feature-development
curve is no longer mistaken for the shipped result: left = feature progress at
±2s, right = shipped detector at the ±20s tolerance the pipeline uses.

2026-08-11 20:54:15 +02:00

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