build_finder_eval.py measures whether the loop finder surfaces the windows PLN
actually cut, using the correlation engine's provenance map (#12) as ground truth
at scale. Metric v2: dedup GT into distinct sampled windows (PLN cuts many
overlapping loops per stem), give the finder N≥#distinct candidates so recall isn't
candidate-capped, and also report precision.

Result on the 8 most-cut stems: recall 0.27 (45/169 distinct windows), precision
0.24 — BELOW the 0.70 v1 target. Honest and diagnostic, not a pass:
- The eval picked the hardest stems by design (ranked by #cuts) — CHOP-HEAVY sources
  (14–42 distinct cuts each: Doors, Xxplosive, MC Fioti, Brubeck). PLN chops them into
  short, often sub-bar pieces; the finder targets 2/4/8-bar LOOPS, so it can't
  reproduce sub-bar chops.
- Vocal stems worst (Doors/vocals 0.06) vs rhythmic best (Gil Scott-Heron 0.56): the
  per-stem PLP beat grid is weak on sparse-onset vocals → poor candidate windows.
- Loop choice is taste-driven anyway (house rule: finder suggests, human picks).

Next steps surfaced (new task): (1) borrow the beat grid from drums/full-mix for all
stems; (2) add a sub-bar onset-driven "chop mode". The harness is the katana for both.