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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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Quality and Safety 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.

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.

516 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.
516 works in the cohort · of 4,299,418page 7 of 11

Labels cover 2 of 516 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 516 of 516 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
Human Factors in the Wild
Yan Xiao, Shanqing Yin, Rollin J. Fairbanks, Laurie Wolf, Anjum Chagpar, C. Adam Probst
2013· article· en· Proceedings of the Human Factors and Ergonomics Society Annual Meeting· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Cardiac Markers
Alan H.B. Wu
2003· book· en· Humana Press eBooks· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Quantified Methodology of Health
Igor Schagaev, Vadim Geurkov
2023· preprint· en· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
A Review on Next Generation eCTD – eCTD v4.0
Nikkitha Sudesamithiran
2023· review· en· International Journal of Drug Regulatory Affairs· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Managing “change” in HD unit
S.J. Christopoulou
2005· article· en· Hemodialysis International· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Implementation Requirements
Linda Bird
2025· book-chapter· en· Health information technology standards· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Exam Day Preparations
A. Lee Foote
2015· book-chapter· en· Elsevier eBooks· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Occupational Health Informatics
Anil Adisesh, Christopher J. O. Baker
2023· article· en· Occupational Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affaboutno abstractunlabeled
Academic Programs in Clinical Engineering in Canada
Varsha Chaugai, Timothy J. Zakutney, Adrian D. C. Chan, Andy Adler
2013· article· en· CMBES Proceedings· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
ENVRIplus D10.1: Guidelines on access to RIs
Simone Galiardi, Sabine Philippin, Rosa Maria Petracca Altieri, Mylène Ndisi, Lilith Kuckero, Anders Tjulin
2019· report· en· HAL (Le Centre pour la Communication Scientifique Directe)· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Background to Human Factors in Healthcare
Avi Parush, Debi Parush, Roy Ilan
2017· book-chapter· en· Synthesis lectures on assistive, rehabilitative, and health-preserving technologies· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affgemma · no categorygpt · no categorymodels split
Quantified Methodology of Health
Igor Schagaev, Vadim Geurkov
2023· preprint· en· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Toronto Hospital Alertness Test
Colin M. Shapiro, Christine Auch, Marlene Reimer, Leonid Kayumov, Ronald J. Heslegrave, Nada Huterer +2 more
2006· dataset· en· PsycTESTS Dataset· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s1544-8800(13)70016-2
2000· article· en· Time to knit· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About