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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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Simulation-Based Education in Healthcare
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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
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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.

2,300 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.
2,300 works in the cohort · of 4,299,418page 34 of 46

Labels cover 5 of 2,300 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 2,300 of 2,300 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.

afffundvenueunlabeled
Endoscopy simulation for pre-clerkship students
Amit Persad, Lalit Verma, Rabindranath Persad
2019· article· en· Canadian Medical Education Journal· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Abstracts
Simone Crooks, Michelle Chiu, John Kim, Gregory L. Bryson, George A. Dumitrascu, Robert Elliott +25 more
2011· article· fr· Canadian Journal of Anesthesia/Journal canadien d anesthésie· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
Comparing the Effectiveness of Multimodal Learning Using Computer-Based and Immersive Virtual Reality Simulation–Based Interprofessional Education With Co-Debriefing, Medical Movies, and Massive Online Open Courses for Mitigating Stress and Long-Term Burnout in Medical Training: Quasi-Experimental Study
Sirikanyawan Srikasem, Sunisa Seephom, Atthaphon Viriyopase, Phanupong Phutrakool, Sirhavich Khowinthaseth, Khuansiri Narajeenron
2025· article· en· JMIR Medical Education· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Two Paths to Competency Validation
Briyana L. M. Morrell, Nancy Campbell
2016· article· en· Journal for Nurses in Professional Development· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Reply to
Karin Graeser, Lars Konge
2014· letter· en· European Journal of Anaesthesiology· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
affno abstractunlabeled
Simulation for Pharmacy
Marie‐Laurence Tremblay, Marie-Claude Boivin
2019· book-chapter· en· Elsevier eBooks· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Erratum to: Textbook of Critical Care, 6th Edition
Lauralyn McIntyre, Amanda Roze des Ordons
2012· erratum· en· Canadian Journal of Anesthesia/Journal canadien d anesthésie· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affaboutunlabeled
Essential Primary Health Care Skills
Erin Ziegler, Amina Silva, Sarah Pirani, Jane Tyerman, Marian Luctkar‐Flude
2025· article· en· Nurse Educator· Medicine
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About