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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.

2,224 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.
2,224 works in the cohort · of 4,299,418page 10 of 45

Labels cover 25 of 2,224 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 2,224 of 2,224 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
Perceptions of a faculty mentorship programme
Lil Miedzinski, Winnie Wing-Sze Wong, J Charles Morrison
2009· article· en· Medical Education· Medicine
machine prediction:candidate · noneconsensus · none
7
citations
venueno affunlabeled
The inquiry model of medicine
Alex Broadbent
2019· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · metaresearchconsensus · none
7
citations
affunlabeled
Perspective
Shannon E. MacDonald, Heather Sharpe, Keiko Shikako‐Thomas, Bodil Katrine Larsen, Lyndsay Jerusha MacKay
2012· article· en· Academic Medicine· Medicine
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
The Push to Subspecialize
Michael Goldfarb
2014· editorial· en· Journal of the American College of Cardiology· Medicine
machine prediction:candidate · noneconsensus · none
7
citations
venueaboutno affunlabeled
From bedside to bench and back again
R. Collier
2011· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · metaresearchconsensus · none
6
citations
affno abstractunlabeled
All journals need to correct errors
Jonathan D. Linton
2013· letter· en· Nature· Medicine
machine prediction:candidate · metaresearch+research_integrityconsensus · none
6
citations
affunlabeled
Key factors of clinical research network capacity building
Guowei Li, Qianyu Wu, Yanling Jin, Thuva Vanniyasingam, Lehana Thabane
2018· review· en· ˜The œJournal of venomous animals and toxins including tropical diseases· Medicine
machine prediction:candidate · metaresearchconsensus · none
6
citations
aboutno affunlabeled
Why a journal oversight committee?
John Hoey, Anne Marie Todkill
2003· article· en· PubMed· Medicine
machine prediction:candidate · metaresearchconsensus · none
6
citations
venueaboutno affunlabeled
Canadian cardiac journal turns “predatory”
Tom Spears
2014· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · metaresearch+research_integrityconsensus · none
6
citations
venueno affunlabeled
Working for Free
John Russell Taylor
2004· article· en· Canadian Journal of Plastic Surgery· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
6
citations
affunlabeled
The future of medical professionalism
John R. Williams
2009· article· en· South African Journal of Bioethics and Law· Medicine
machine prediction:candidate · noneconsensus · none
6
citations
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