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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.

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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
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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 36 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.

affaboutunlabeled
What is a good death?
Anders Ganstal
2003· letter· en· BMJ· Health Professions
machine prediction:candidate · noneconsensus · none
4
citations
aboutno affunlabeled
A prescription for poverty
Jane Parry
2016· article· en· BMJ· Health Professions
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Interventional pharmacotherapy
Roger Philipp
2003· review· en· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
fundno affno abstractunlabeled
States cannot negotiate a pandemic treaty alone
Tim Fish Hodgson, Magdalena Sepúlveda Carmona, Mike Podmore
2022· article· en· BMJ· Social Sciences
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Pyoderma gangrenosum
Katie Yeung, Emily OConnor, Peter Hull
2023· article· de· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Reducing sunbed use in young people
J M. Elwood, R Gallagher
2010· letter· en· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Ectopic pregnancy
S. Al-Jabri, M. Malus, Togas Tulandi
2010· article· en· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Web: The sum of my parts
Charles Weijer
2000· article· en· BMJ· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
3
citations
affunlabeled
Turning a blind eye:Authors' reply
Dean Fergusson, Kathleen Cranley Glass, Duff Waring, Stan Shapiro
2004· article· en· BMJ· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
What’s the need?
2008· letter· en· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Diagnosing and defining obesity
Oliver Mytton, Denise Campbell‐Scherer, Ian Reckless, Clare Llewellyn
2025· editorial· en· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Robots, radiologists, and results
Vanessa Rampton, Athena Ko
2022· editorial· en· BMJ· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Authors’ reply to Rafi
Joel G. Ray, Emily Bartsch
2016· letter· de· BMJ· Health Professions
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
The processing cycle
Deana Midmer
2002· article· en· BMJ· Engineering
machine prediction:candidate · noneconsensus · none
3
citations
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