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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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Health Sciences Research and Education
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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.

2,679 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.
2,679 works in the cohort · of 4,299,418page 51 of 54

Labels cover 60 of 2,679 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 2,679 of 2,679 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.

affvenueaboutunlabeled
The EXTRA Difference: Leadership Development
Jessica Kerr, Mary Ellen Jeans
2006· article· en· Nursing leadership· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Ethics in publishing
John M. Fitzpatrick
2013· article· en· Canadian Urological Association Journal· Health Professions
machine prediction:candidate · research_integrityconsensus · none
0
citations
afffundunlabeled
Advocacy in Outreach: A BHSc Outreach Case Competition 2023
Aashna Agarwal, Neil Lin, A Abdi
2023· article· en· Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
AMS Panel discussion on Undergraduate Research
Bianca Chauhan, Cory Laverty, Caroline Marful
2018· article· en· Inquiry Queen s Undergraduate Research Conference Proceedings· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A letter to Denis Lynn
Patrick J. Keeling, Vittorio Boscaro, Floyd T. Bardell, Fabien Burki, cho anna, Elizabeth C. Cooney +42 more
2020· letter· en· Aquatic Ecosystem Health & Management· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Proficiency-based training: Parameters educators should consider
Ryan Brydges, Allison Kurahashi, Vera Brümmer, Lisa Satterthwaite, Roger Classen, Adam Dubrowski
2007· article· en· Journal of the American College of Surgeons· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Modul Sosialisasi Interprofession Education
2021· other· id· Zenodo (CERN European Organization for Nuclear Research)· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Building Research Capacity Among Community College Nursing Faculty
Jennifer Innis, Jasmine Balakumaran, Roya Haghiri‐Vijeh, Michelle C. Hughes, Krista Kamstra‐Cooper, Audrey Kenmir +2 more
2021· article· en· Journal of innovation in polytechnic education.· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About