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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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Healthcare Systems and Challenges
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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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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.

482 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.
482 works in the cohort · of 4,299,418page 2 of 10

Labels cover 3 of 482 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 482 of 482 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.

affvenueunlabeled
Recruiting for Engagement in Health Policy
Joanna Massie, Katherine Boothe
2024· article· en· Healthcare policy· Health Professions
machine prediction:candidate · metaresearchconsensus · none
5
citations
aboutno affunlabeled
A major failure of scientific governance
Richard Smith, Fiona Godlee
2015· editorial· en· BMJ· Health Professions
machine prediction:candidate · metaresearch+research_integrityconsensus · none
5
citations
afffundunlabeled
Rebuttal to Douglas and Elliott
Robert Hudson
2022· article· en· Journal for General Philosophy of Science· Health Professions
machine prediction:candidate · noneconsensus · none
5
citations
affaboutunlabeled
Canada needs a national COVID-19 inquiry now
David N. Fisman, Jillian Horton, Matthew Oliver, Mark Ungrin, Julia M. Wright, Dick Zoutman
2024· review· en· BMC Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
4
citations
aboutno affunlabeled
Farewell to dodging and weaving
Nicholas Timmins
2007· article· en· BMJ· Health Professions
machine prediction:candidate · noneconsensus · none
3
citations
venueaboutno affunlabeled
Network tackles overprescribing
Lauren Vogel
2016· article· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
venueaboutno affunlabeled
Lament for a health care system
2005· editorial· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Policy lessons from physicians’ strikes
Gregory P. Marchildon
2013· editorial· en· Israel Journal of Health Policy Research· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Bound to care
Chris Cox
2006· article· en· Nursing Standard· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Tips for middle leaders
Chris Byrne
2015· article· en· SecEd· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
The United Kingdom's mask crusader
Ellen Ruppel Shell
2020· article· en· Science· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About