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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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Innovations in Medical Education
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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.

6,256 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.
6,256 works in the cohort · of 4,299,418page 87 of 126

Labels cover 27 of 6,256 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 6,256 of 6,256 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
Focus on faculty development
Marcel D’Eon, Heather Buckley, Katherine Wisener
2024· editorial· en· Canadian Medical Education Journal· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Current Medical Education -A Bird’s Eye View
Prema Padmanabhan, Kowale A.N
2024· article· en· International Journal of Clinical and Medical Education Research· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affvenueunlabeled
Adaptive family physicians
Cheri Bethune, Wendy Graham, Thomas Heeley
2021· article· en· Canadian Family Physician· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Active Engagement
Abhinav Sharma, Kishan S. Parikh, Christopher B. Fordyce
2016· editorial· en· Journal of the American College of Cardiology· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
How to take a medical history
Peter Washer
2009· book-chapter· en· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Commentaries and conversations
Rachel Ellaway
2025· editorial· en· Advances in Health Sciences Education· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affvenueaboutunlabeled
Tips for Facilitating Morning Report
Luke Devine, Wayne L. Gold, Andrea Page, Steven L. Shumak, Brian M. Wong, Natalie Wong +1 more
2017· article· en· Canadian Journal of General Internal Medicine· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Hot Seat Diagnosis
Rachel Han, Julia Keith, Elzbieta Slodkowska, Sharon Nofech‐Mozes, Bojana Djordjevic, Carlos Parra‐Herran +5 more
2021· article· en· Archives of Pathology & Laboratory Medicine· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
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How this was built: Screen · Findings · About