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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.

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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Lipid metabolism and disorders
Retraction
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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
venuejournal
aboutaboutness

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

712 results · 1 filter active ·
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20002025
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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.
712 works in the cohort · of 4,299,418page 14 of 15

Labels cover 2 of 712 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 712 of 712 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.

venueno affno abstractunlabeled
10.1016/s1155-1917(04)38512-0
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Troodontidae Gilmore 1924
2003· article· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Lipemia retinalis after alcohol abuse
Juan Ángel Moreno-Gutiérrez, Ana Flores-Márquez, Carlos Rocha‐de‐Lossada
2022· article· en· Canadian Journal of Ophthalmology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Approach to Hypertriglyceridemia
Robert A. Hegele
2023· book-chapter· en· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s1155-1941(20)82782-6
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Angiopoietin–1 promotes pericyte survival and activation
Philip Hykin, G M Smith, Oksana Nalovina, Jun Cai, S R Boyd, M. Boulton
2004· article· en· Investigative Ophthalmology & Visual Science· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Le mythe de l’Hyperloop
Matthew Sorola, Guilain Praseuth, Alix Werthauer
2024· article· fr· Revue française de gestion· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/b978-2-294-73068-9.00002-5
2000· book-chapter· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s1155-1941(19)30274-4
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s1155-1941(19)30042-3
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About