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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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Clinical Reasoning and Diagnostic Skills
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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.

1,287 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.
1,287 works in the cohort · of 4,299,418page 17 of 26

Labels cover 7 of 1,287 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 1,287 of 1,287 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
Reducing length of stay and satisfying learner needs
Lisa Shepherd, Saad Chahine, Michelle Klingel, Elaine Zibrowski, Allison Meiwald, Lorelei Lingard
2016· article· en· Perspectives on Medical Education· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Lies, damned lies, and statistics
Geoff Norman
2018· article· en· Perspectives on Medical Education· Medicine
machine prediction:candidate · metaresearchconsensus · none
3
citations
affno abstractunlabeled
P115: Bounceback reports-improving patient care
Fausto J. Pinto, Marie-Renée B-Lajoie
2018· article· en· Canadian Journal of Emergency Medicine· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
How doctors think
Brent M McGrath
2009· article· en· Canadian Family Physician· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
Supervision of clinical reasoning
Marie‐Claude Audétat, Suzanne Laurin
2010· article· en· Canadian Family Physician· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Can Cognitive Assessment Games Save Us From Cognitive Decline?
Mark Chignell, J. Bruce Morton, Monika Kastner, J.S. Lee
2021· article· en· Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care· Medicine
machine prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About