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

3,522 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.
3,522 works in the cohort · of 4,299,418page 69 of 71

Labels cover 18 of 3,522 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 3,522 of 3,522 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.

affaboutno abstractunlabeled
A Canadian on Capitol Hill
Nadine Abi‐Jaoudeh
2006· article· en· Journal of the American College of Radiology· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
In Reply to Hyder
Asim Alam, Jessica J. Lui, Chaim M. Bell
2017· letter· en· Academic Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Rueful Valedictory Repentance
Kieran Walsh
2012· letter· en· Academic Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
Residency cuts reveal workforce plan flaws
Lauren Vogel
2015· article· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · metaresearchconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s1544-8800(06)70798-9
2000· article· en· Time to knit· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Career Outcomes and Diversity: New Scholarship and Directions
Maike Andresen, Janine Bosak, Douglas T. Hall, Béatrice van der Heijden, Bernadeta Goštautaitė, Najung Kim +47 more
2024· article· en· Academy of Management Proceedings· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affvenueaboutunlabeled
Aider à améliorer le jumelage du SCJR
Dianne Delva
2021· article· fr· Canadian Family Physician· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
5 Calgary, fired up for change
2023· book-chapter· en· University of Calgary Press eBooks· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
In Reply to Fyfe and Douglass
Melanie Raffoul, Gillian Bartlett‐Esquilant, Robert L. Phillips
2020· letter· en· Academic Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
News @ a glance
S Duggal
2008· article· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueaboutno affno abstractunlabeled
10.1016/s0765-2046(97)80138-4
2000· article· en· Time to knit· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueaboutno affunlabeled
The Newfoundland and Labrador Health Accord
Stephen
2022· article· en· Health Reform Observer - Observatoire des Réformes de Santé· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
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