# External evidence (2026-09-29)

Independent-source media used to stress the identity pipeline. **None of this is
Tier 2.** DECISION.md's Tier 2 is a second labelled store visit; these are
`external_proxy` artifacts, and every manifest here says so.

| Directory | What it holds |
|---|---|
| `other-mayo/` | 8 accepted images for `sku_l04`, `sku_l07`, `sku_l09` from 6 source domains, plus the scored result |
| `l12-reconciliation/` | What `sku_l12` actually is, from the shelf tag and package pixels |
| `kewpie/` | 12 accepted images for six SKUs from 6 source domains, plus the scored result. One is now enrolled, so it is excluded from scoring. |
| `tier3-sources/` | Two reusable pan clips and 11 rejected candidates for a future Tier-3 replay |

## Leak checks

Two, both in `code/eval_external.py`, both run before any number is reported:

- **Against the evaluation photo.** Every image is template-matched against
  `add/image6.jpg`. The highest score across all 20 is 0.675 (`sku_l07_1`), and
  the 0.95+ band that identifies a crop of the evaluation photo is empty.
- **Against the catalog.** An image that has since been enrolled is refused
  rather than scored. `kewpie/sku_l06_1.jpg` is one: it is now the enrolled l06
  view, so scoring it would be training accuracy wearing a held-out label.

## Result: 19 scored, 0 false accepts

    .venv/bin/python code/eval_external.py --stock stock-lopia-clean \
        data/external-eval/kewpie data/external-eval/other-mayo

| Set | Scored | Correct | Abstain | False accepts | Leaked |
|---|---|---|---|---|---|
| `kewpie/` | 11 | 8 | 3 | **0** | 1 |
| `other-mayo/` | 8 | 4 | 4 | **0** | 0 |
| **Total** | **19** | **12** | **7** | **0** | **1** |

Two things this establishes that the image6 shelf cannot:

- **`sku_l07` is answered with no enrolled image.** Both l07 images accept
  through the text lane alone: `sku_l07_1` reads ラッキー フヨネーズ, and
  `sku_l07_2` reads the rear label's 製造者：丸和油脂株式会社 with 内容量：200g.
  The catalog row is 丸和油脂 ラッキーマヨネーズ 200g, so the manufacturer and
  the size together name it. This is the text lane's coverage claim - that a
  product with no reference image can still be named - holding on data that was
  not used to build it.
- **The l04 abstentions are correct behaviour, not a miss.** l04 has no
  enrolled image either, and its reads are weak: `sku_l04_2` reads only
  コと旨 タ 味 (all rows score 0.0), and `sku_l04_4` reads the rear label with
  やまや garbled to まや, scoring 0.379 - below the accept line. Abstaining on
  a weak read is the designed outcome.

`sku_l07_2` accepts with a negative local score (-0.55) on text evidence alone.
That is the lane doing its job, but it is worth naming: the accept rests on two
matched tokens (manufacturer + size), not on geometry.

## What is still missing

No external source gives per-SKU identity for the whole catalog, and no
reusable clip combines the target category with shelf-distance text
resolution. The Tier-2 and Tier-3 gates in DECISION.md still need the
operator's own recorded walks.