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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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Studies in health technology and informatics
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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.

990 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.
990 works in the cohort · of 4,299,418page 6 of 20

Labels cover 2 of 990 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 990 of 990 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.

affaboutunlabeled
OCRx: Canadian Drug Ontology
Jean Noël Nikiema, Man Qing Liang, Philippe C Després, Aude Motulsky
2021· book-chapter· en· Studies in health technology and informatics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
7
citations
afffundunlabeled
Building a Disease Knowledge Graph
Enayat Rajabi, Somayeh Kafaie
2023· article· en· Studies in health technology and informatics· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Nursing Informatics Research Trends: Findings from an International Survey
Laura‐Maria Peltonen, Raji Nibber, Lorraine J. Block, Charlene Ronquillo, Erika Lozada‐Perezmitre, Adrienne Lewis +20 more
2021· article· en· Studies in health technology and informatics· Health Professions
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
7
citations
affunlabeled
Reason for Use: An Opportunity to Improve Patient Safety
Reicelis Casares Li, Thana Hussein, Ashley Bancsi, Kelly Grindrod, Catherine M. Burns
2019· article· en· Studies in health technology and informatics· Health Professions
machine prediction:candidate · noneconsensus · none
6
citations
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How this was built: Screen · Findings · About