How well it works

On held-out recalls, when a title can't settle it, Recall Reach asks instead of guessing in 11 of 12 pairs. A plain word match guesses in 11 of 12.

12 pairs where the title can't settle it
83 look-alikes, which are not the recalled product
Held-out pairsRecall ReachWord match
A look-alike reaches the seller37 of 83 (45%)
34 to 55%
45 of 83 (54%)
44 to 65%
A look-alike could reach a family2 of 83 (2%)
1 to 8%
45 of 83 (54%)
44 to 65%
Claude labelled all 285 pairs, from 75 recalls. One labeller. No person has audited them. A second model from OpenAI (gpt-6.1-sol), blind to Claude's labels, checked 50 of them: it agreed on 34, said the title can't settle it on the other 16, and called none of Claude's look-alikes the recalled product. The files.
Title can't settle it: asks11 of 12 (92%)
65 to 99%
0 of 12 (0%)
0 to 24%
Title can't settle it: calls it a match0 of 12 (0%)
0 to 24%
11 of 12 (92%)
65 to 99%
Title can't settle it: misses it1 of 12 (8%)
1 to 35%
1 of 12 (8%)
1 to 35%

Ranges are 95% Wilson intervals. Word match flags whatever the search finds, with no way to abstain.

These are first-run numbers. We set the held-out recalls aside on Nov 5, and later rule changes left these numbers the same. One held-out recall's CPSC sentence (26054) is used as an example in one rule's test.

Where it was wrong

On a wider screen, this is a table of all 38.

When a title states the model

We searched a public product index for 40 recalled models, one search each. Of 311 products found, 0 had the model in the title. So these titles are built from each recall's own words, and are not real listings. They show the matcher reads a model when one is stated, and nothing more.

60 recallsRecall ReachWord match
Title states the recalled model: confirmed52 of 60 (87%)
76 to 93%
60 of 60 (100%)
94 to 100%
Model one character off: wrongly confirmed0 of 53 (0%)
0 to 7%
53 of 53 (100%)
93 to 100%

The other 8 ask instead. On 6 of them CPSC limits the recall within the model, by VIN, a code or a look-up, so the model alone can't settle it.

An earlier version confirmed 58 of these 60. That was wrong for 6 recalls CPSC limits within the model, so it asks on those now.

What Claude says about these

Claude read the 48 held-out pairs that reach a seller. Its finding is text for the seller to read. It changes nothing above.

Claude also wrote these labels, so this table shows it agrees with itself as much as with the truth. A person's audit is what would make it independent.

Claude saidOn look-alikesOn pairs the title can't settle
Same product0 of 37 (0%)
0 to 9%
0 of 11 (0%)
0 to 26%
Can't tell22 of 37 (59%)
43 to 74%
11 of 11 (100%)
74 to 100%
Different product15 of 37 (41%)
26 to 57%
0 of 11 (0%)
0 to 26%

Where it falls short: on 22 of 37 look-alikes Claude said it can't tell, so the seller still has to ask. It called none of the 48 the same product, but with Claude's own labels that isn't proof.

What this does not show

Every miss, by name

Could reach a family

Missed, where the title can't settle it

Reached the seller

Run it yourself with pnpm eval. A test fails if these numbers stop matching what the code produces. Home

Separate from these numbers: what sellers said about its flags.