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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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Primary Care and Health Outcomes
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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
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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.

4,685 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.
4,685 works in the cohort · of 4,299,418page 42 of 94

Labels cover 32 of 4,685 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 4,685 of 4,685 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.

affvenueaboutunlabeled
Canada’s future health care system
Donald J. Willison, Braden O’Neill, Michelle Greiver, Frank Sullivan
2018· letter· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
A suitable case for treatment
John Launer
2007· article· en· QJM· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
Patient care in the information age.
David Keegan
2015· letter· en· PubMed· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
venueaboutno affunlabeled
The authors respond
Simon J. Walter, David M. Studdert
2012· article· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affno abstractunlabeled
The time in your life: use it wisely
Dennis J. Lutz
2010· article· en· American Journal of Obstetrics and Gynecology· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
Raising the bar for health leadership in Australia
Alberto Rodriguez-Moldes Sebastian
2015· article· en· Asia Pacific Journal of Health Management· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
Community Outreach and Patient Empowerment
Tammy Yazzie, Alberta Long, Mae‐Gilene Begay, Shirley Cisco, Hannah Sehn, Sonya Shin +1 more
2011· article· en· Journal of Ambulatory Care Management· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
venueaboutno affunlabeled
Patient-based funding model endorsed
Roger Collier
2008· article· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
Mental health needs targeted federal funds
Shannon Lough
2015· article· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Integrated People-Centered Health Care
Katherine Rouleau, Shatha Albeik, Sayed Masoom Shah, Kenneth Yakubu, Akihiro Seita
2022· book-chapter· en· Cambridge University Press eBooks· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affno abstractunlabeled
An Action Plan for Reforming Healthcare in Canada
Don Drummond, Talitha Calder
2017· book-chapter· en· McGill-Queen's University Press eBooks· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
The complexity of physician power
Laura Nimmon
2024· letter· en· Science· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About