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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
Retraction
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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.

2,300 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.
2,300 works in the cohort · of 4,299,418page 43 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.

affno abstractunlabeled
Simulations in clinical neurosciences
Ljuba Stojiljković, Jamie L. Uejima, Kan Ma
2025· book-chapter· en· Elsevier eBooks· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Constructing Shared Mental Models in High-Acuity Clinical Trajectories: A Narrative Review and Proposed Framework for Multidisciplinary Simulation Integrating Pre-Hospital, Emergency, and Surgical Disciplines
Albalihed Mohanad Mtrokh, Abdulkhaliq Mashni Alamri, Emad Atallah Oudah Almashari, Abdalmalek Mtrouk H Alblyhed, Sultan Ghanem Alruwaili, Khalid Alanazi +9 more
2025· article· Saudi Journal of Medicine and Public Health· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Quality Feedback
Dina Kurzweil, Diane Seibert, Godsgrace Tetteyfio, Brandon Michael Henry, Danette F Cruthirds
2022· article· en· Nurse Educator· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affvenueno abstractunlabeled
“Who would you like me to call?”
Adam Bobrowski
2023· article· en· Canadian Urological Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
In reply: A view from the middle of the totem pole
M. Dylan Bould, Stephanie Sutherland, Devin Sydor, Viren N. Naik, Zeev Friedman
2015· letter· en· Canadian Journal of Anesthesia/Journal canadien d anesthésie· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
A RAY OF HOPE - Paul Hawken
2007· other· en· Bulletin of Miscellaneous Information (Royal Gardens Kew)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
The Future of Simulation
Ann Russell, Jordan Holmes, Nancy McNaughton, Kerry Knickle, Juanita Richardson
2023· book-chapter· en· Comprehensive healthcare simulation· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Simulation Scenario Design
J. Damian Paton-Gay, Peter G. Brindley, Lawrence M. Gillman
2025· book-chapter· en· Medicine
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About