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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

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The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Rosa P: A digital library for transportation research (United States Department of Transportation)
Topic
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

affaffiliation
fundfunder
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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

119 results · 1 filter active ·
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20002024
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
119 works in the cohort · of 4,299,418page 3 of 3

Labels cover 1 of 119 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 119 of 119 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

aboutno affunlabeled
Alternative jet fuel scenario analysis report
2012· other· en· Rosa P: A digital library for transportation research (United States Department of Transportation)
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Class 1 railroad statistics, 2008
2010· other· en· Rosa P: A digital library for transportation research (United States Department of Transportation)· Physics and Astronomy
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
U.S.- Canada Land Ports of ENtry (LPOEs): Washington
2017· other· en· Rosa P: A digital library for transportation research (United States Department of Transportation)
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affno abstractunlabeled
U.S. - Canada Land Ports of Entry (LPOEs): New York
2017· other· en· Rosa P: A digital library for transportation research (United States Department of Transportation)
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affno abstractunlabeled
U.S. - Canada Land Ports of Entry (LPOEs): Idaho
2017· other· en· Rosa P: A digital library for transportation research (United States Department of Transportation)· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Employee Assistance Program for Transit Systems
2015· report· en· Rosa P: A digital library for transportation research (United States Department of Transportation)
machine prediction:candidate · noneconsensus · none
0
citations
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