# M1 Validation Gate

Before widening past the hard sample, trip-cluster must clear a quantified bar on a
**deliberately hard slice** — a GPS-poor, multi-year, low-density window (a well-remembered
old trip plus its surrounding everyday photos), **not** the easy phone-era last trip.

## Protocol

1. `categorize ingest --from <hard-window-start> --to <hard-window-end>` (or `--tag <old-trip>`).
2. `categorize cluster`, then `categorize serve`.
3. Hand-label the slice: the true trip boundaries + which surrounding photos are non-trip.
4. Compare candidate clusters against the labels.

## Acceptance bar (record actual numbers per run)

| Metric | Definition | Target |
|--------|------------|--------|
| Trip-boundary precision | proposed boundaries that are real | ≥ 0.8 |
| Trip-boundary recall | real boundaries proposed | ≥ 0.8 |
| Coverage-flag recall | in-window missing-tag assets surfaced | ≥ 0.9 |
| Over-split rate | extra clusters per real trip | ≤ 0.5 |
| False-cluster rate | clusters that are pure noise | ≤ 0.1 |

If unmet, tune `--gap-factor` / seed-span / confidence thresholds — do **not** widen the
backlog. See the F4 open question (everyday cluster blow-up): observe the real cluster
count on a representative subset first, then choose the surfacing/collapsing strategy.