Write the desktop session's brief for Tier 3 detection

The fingerprinting runs on a device now and has still confirmed nothing for
a real show. That is an open question, not a known bug, and answering it
needs the prototype rather than the app -- only the prototype can show what
a parameter change costs in false positives, which is the number that
matters here.

docs/detection-findings.md collects what this round established: that the
pipeline works, that the confirmation threshold earns its place, and the
finding that reframes the problem -- dynamic ad insertion means the same
Grass Apes came back 29:34 on one fetch and 27:39 on another, so ad content
and the offset of everything behind it differ per request. It lists the
experiments in order, including using insertedAdMs as ground truth for the
midroll scan, and what not to touch.

Linked from the known-gaps list, which is where a future session looks.

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

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