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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 disparities and outcomes
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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.

4,167 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.
4,167 works in the cohort · of 4,299,418page 21 of 84

Labels cover 28 of 4,167 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 4,167 of 4,167 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.

afffundaboutno abstractunlabeled
Cohort Profile: The British Columbia Generations Project (BCGP)
Anar Dhalla, Treena McDonald, Richard P. Gallagher, John J. Spinelli, Angela Brooks‐Wilson, Tim K. Lee +5 more
2018· article· en· International Journal of Epidemiology· Social Sciences
machine prediction:candidate · noneconsensus · none
35
citations
affno abstractunlabeled
Assessing health-related resources in senior living residences
Jacqueline Kerr, Jordan Carlson, James F. Sallis, Dori E. Rosenberg, Chikarlo Leak, Brian E. Saelens +5 more
2011· article· en· Journal of Aging Studies· Social Sciences
machine prediction:candidate · noneconsensus · none
34
citations
affunlabeled
Ubiquitous Yet Unique
Yoshitaka Iwasaki, Jennifer Mactavish
2005· article· en· Rehabilitation Counseling Bulletin· Social Sciences
machine prediction:candidate · noneconsensus · none
34
citations
affunlabeled
Education and Coronary Heart Disease Risk
Eric B. Loucks, Stephen E. Gilman, Chanelle J. Howe, Ichiro Kawachi, Laura D. Kubzansky, Rima E. Rudd +4 more
2014· article· en· Health Education & Behavior· Social Sciences
machine prediction:candidate · noneconsensus · none
34
citations
affvenueaboutno abstractunlabeled
Health Status of Older Chinese in Canada
Daniel W. L. Lai
2004· article· en· Canadian Journal of Public Health· Social Sciences
machine prediction:candidate · noneconsensus · none
33
citations
affunlabeled
Validation of the RIS Eldercare Self-Efficacy Scale
Benjamin H. Gottlieb, Jennifer Rooney
2003· article· en· Canadian Journal on Aging / La Revue canadienne du vieillissement· Social Sciences
machine prediction:candidate · noneconsensus · none
33
citations
afffundno abstractgemma · no categorygpt · no categorymodels agree
Cohort Profile: The Care Trajectories—Enriched Data (TorSaDE) cohort
Alain Vanasse, Yohann Chiu, Josiane Courteau, Marc Dorais, Gillian Bartlett, Kristina Zawaly +1 more
2020· article· en· International Journal of Epidemiology· Social Sciences
machine prediction:candidate · noneconsensus · none
33
citations

How this was built: Screen · Findings · About