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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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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
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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.

2,802 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.
2,802 works in the cohort · of 4,299,418page 47 of 57

Labels cover 38 of 2,802 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 2,802 of 2,802 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.

affunlabeled
Authors’ reply to Thilagnathan
Joel G. Ray, Emily Bartsch
2016· letter· de· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Author's reply
Jeffrey J. Perry
2010· article· en· BMJ
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Thomas Henry Eustace
John C. Eustace
2003· article· eu· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Authors’ reply to Datta
Giulia M. Muraca, K.S. Joseph
2023· letter· de· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Painful blisters on the hand
Yuliya Velykoredko, David N. Adam
2013· article· en· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Colin Andrew Ramsay
Philipp Meisner
2003· article· en· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Writing to patients can cause upset
Peter Idagu, Itoro Udo
2020· letter· en· BMJ· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Peter John Mowbray
Derek Mowbray
2003· article· en· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A man with rust coloured urine and normocytic anaemia
Sarah Case, Thomas J. Johnston, Michael O’Sullivan, Will Thomas, Oliver Wiseman
2015· article· en· BMJ· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affgemma · no categorygpt · no categorymodels agree
Mark Arnold Wainberg
Barbara Kermode-Scott
2017· article· en· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Winners and losers
Mary E Black
2012· article· en· BMJ· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Ranger Michael Whelan
Tim Whelan
2003· article· de· BMJ· Arts and Humanities
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
NHS overspend reaches £2.3bn
Susan Mayor
2016· article· en· BMJ· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
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How this was built: Screen · Findings · About