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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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Journal of Continuing Education in the Health Professions
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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.

affaffiliation
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

377 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.
377 works in the cohort · of 4,299,418page 6 of 8

Labels cover 1 of 377 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 377 of 377 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.

affunlabeled
Remediation in Practice: A Polarity to be Managed
Gisèle Bourgeois‐Law, Lara Varpio, Pim W. Teunissen, Glenn Regehr
2021· article· en· Journal of Continuing Education in the Health Professions· Health Professions
machine prediction:candidate · noneconsensus · none
7
citations
affaboutunlabeled
The opportunity for improvement
Craig Campbell
2003· article· en· Journal of Continuing Education in the Health Professions· Health Professions
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Learning With Patients, Students, and Peers
Anna Ryan, Rose Hatala, Elizabeth Molloy
2020· article· en· Journal of Continuing Education in the Health Professions· Medicine
machine prediction:candidate · noneconsensus · none
6
citations
affaboutunlabeled
Do continuing medical education articles foster shared decision making?
Michel Labrecque, Valérie Lafortune, Judith Lajeunesse, Anne-Marie Lambert-Perrault, Hermes Manrique, Johanne Blais +1 more
2010· article· en· Journal of Continuing Education in the Health Professions· Health Professions
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Numeracy Education for Health Care Providers: A Scoping Review
Casey Goldstein, Nicole N. Woods, Rebecca MacKinnon, Rouhi Fazelzad, Bhajan Gill, Meredith Giuliani +3 more
2023· review· en· Journal of Continuing Education in the Health Professions· Health Professions
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Toward Practice-Based Continuing Education Protocols
Heather Armson, Stefanie Roder, J Wakefield, Kevin W. Eva
2020· article· en· Journal of Continuing Education in the Health Professions· Medicine
machine prediction:candidate · noneconsensus · none
5
citations
affaboutunlabeled
The 2020 JCEHP Award for Excellence in Research
Simon Kitto, Walter Tavares, Elizabeth Franklin, David R. Pieper
2021· editorial· en· Journal of Continuing Education in the Health Professions· Medicine
machine prediction:candidate · noneconsensus · none
4
citations

How this was built: Screen · Findings · About