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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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Global Health Care 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.

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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.

1,663 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.
1,663 works in the cohort · of 4,299,418page 31 of 34

Labels cover 8 of 1,663 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 1,663 of 1,663 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.

affno abstractgemma · no categorygpt · no categorymodels agree
Health State Utility Values Of Hiv Infected Patients In Kenya
Anik R. Patel, M. van der Kop, Richard Lester, David Ojakaa, Patrick Igunza, Richard Gichuki +2 more
2014· article· en· Value in Health· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
fundno affno abstractunlabeled
Guest editors' introduction
Andrew Jones, Owen O’Donnell
2003· article· en· Health Economics· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Guest editors' introduction
Andrew Jones, Owen O’Donnell
2006· article· en· Health Economics· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Frontmatter
Gregory P. Marchildon, Sara Allin
2021· book-chapter· en· University of Toronto Press eBooks· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Boutique Medicine Will Not Save Health Care
Maria C. Raven, Craig G. Smollin
2004· article· en· Emergency Medicine News· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Do You Really Get What You Paid For
Clayton
2010· article· en· The Park Place Economist· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Health Insurance, Liquidity and Growth
Benoı̂t Carmichael, Yazid Dissou
2000· article· en· SSRN Electronic Journal· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Hospital Market Competition and Infant Mortality
Scott A. Lorch, Jeannette Rogowski, Douglas O. Staiger, Jeffrey D. Horbar, Erika M. Edwards, Jochen Profit +1 more
2018· article· en· 7th Annual Conference of the American Society of Health Economists· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About