Score the detectors against what the listener heard, and fix two things it found

Every other number in this project comes from the declared-versus-served length
gap, which says how much advertising a copy carries and nothing about where. A
detector could find the right total in the wrong places and score 100%. The
position check I wrote earlier used the same signal that builds the candidates,
so it was partly circular and structurally blind to the failure it most needed
to see.

The 19 labels are the only statement about *where* that no detector produced:
each is Peter pressing a button at a moment in an episode. listen-score is
read-only, takes the state file, and prints how the published breaks did.

**Its first answer was wrong, and checking rather than reporting it caught
that.** It said 2 of 18 advertisements were covered, which would have meant the
detectors were far worse at position than at totals. They are not: breaks at
829-999 and 1360-1519 against labels at 853-1000 and 1489-1540 -- correct
detections, scored as complete misses because the break stopped a second short
of the label's end. Twelve of the nineteen labels have an end the store itself
documents as a guess, "where a jump happened to land". Scoring against a guessed
end is scoring against noise. A label's start is solid; its end counts only when
measured. 5 of 18 after that.

**A refetch master was blocking the better detector.** Tangle's "The Israeli
elections" has a 229-second gap, a master from a second fetch that carried the
same campaign, and therefore no subtraction candidates at all -- and
findRecurring skipped it because it had a master. Treating "has a master" as
"has a better answer" is wrong when the master is useless. It now skips only
episodes that actually published something.

**The one programme cut is the audio scan's, not the words'.** Its break at
696-708 sits exactly on the stretch Peter said was programme. Worth knowing
before anything else gets blamed for it.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018AwnALZL6bD4VBtATDVv3B

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