Enrolling a packshot from an external set is normal - it is how F-12 was
closed - and it silently turns one of those rows into training data. The
external sets were scored by an ad-hoc script that never checked, so
sku_l06_1.jpg was being reported as a held-out correct accept while being
byte-identical to the enrolled view.
code/eval_external.py now scores those sets with the same leaked() check the
shelf evaluator runs, and refuses a row that has since been enrolled.
That check needed fixing first. Its 64x64 signature fires on two different
photographs of the same product: the l09 rear label from a retailer page sits
19.5 from the enrolled front packshot, under the 20.0 line, while being a
different photograph (resized MAD 26.3). A signature hit is now confirmed by
correlation - a genuine re-cut, re-encode or rescale correlates at 0.99+, that
pair at 0.28 - so the two signals together are decisive where either alone is
not. Verified against both directions: identical, q55 re-encode and 700px
rescale are caught; the different-photo pair is not.
Also adds the van backend (always-argmax, no gate) so the stream comparison in
DECISION.md is reproducible rather than asserted, with two tests pinning that
it answers where the shipped gate abstains and still refuses an empty score set.
External result on the corrected basis: 19 scored, 12 correct, 7 abstain,
0 false accepts, 1 leak excluded. Suite 307 -> 309.
The enrolled sku_l06.jpg showed the superseded 内臓脂肪ケア wrapper. The shelf
and the current retail package both read 内臓脂肪を減らす キューピーフィッテ
210g, so the reference image was of a design the store no longer sells - the
catalog was pointing at the wrong package.
F-12 was recorded as blocked on a capture because Kewpie's own site serves the
old design for that JAN. An independent retailer listing carries the current
one, and it matches the shelf facings exactly (verified by eye against a crop
of add/image6.jpg before enrolling).
Measured effect on the corrected labels: live decision 60% -> 64%, end-to-end
59% -> 62%, full-resolution decision 81% -> 83%. Suite still 307.
Also lands 12 more external-proxy images (six SKUs, two source domains each)
and their scored result. Across both external sets - 20 images - the lane is
13 correct, 7 abstain, 0 false accepts.
Eight images for sku_l04, sku_l07 and sku_l09 from six source domains, scored
through the shipped LocalLaneAdapter and DecisionPolicy against
stock-lopia-clean: 4 correct accepts, 4 abstains, no false accepts.
Leak-tested first: the highest template match of any image against
add/image6.jpg is 0.675, so none is a crop of the evaluation photo.
The result that matters is sku_l07. It has no enrolled image, and both its
images accept through the text lane alone - one reads ラッキー フヨネーズ, the
other the rear label's 製造者：丸和油脂株式会社 with 内容量：200g, which
together name the row 丸和油脂 ラッキーマヨネーズ 200g. The text lane's
coverage claim holds on data that was not used to build it.
The four l04 abstentions are correct behaviour: l04 is also unenrolled and its
reads are weak (one reads only コと旨 タ 味, another scores 0.379 against a
0.45 accept line).
Also records the l12 reconciliation, the Kewpie 450 g research, and two
reusable pan clips with 11 rejected candidates for a future Tier-3 replay.
Nothing here is Tier 2 or Tier 3 and every manifest says so.
