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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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Public Health Policies 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.

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.

1,492 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.
1,492 works in the cohort · of 4,299,418page 23 of 30

Labels cover 10 of 1,492 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 1,492 of 1,492 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.

aboutno affunlabeled
First the report, then the opinions on it
Patrick Sullivan
2003· article· en· Europe PMC (PubMed Central)· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
S103– Promoting evidence‐based decision making in India
Onil Bhattacharyya, Saba Khan, Prabha Sati, Vijayalakshmi Hebbare, Prem K. Mony, Shreelata Rao‐Seshadri +1 more
2010· article· en· Otolaryngology· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
BC Ministry of Health
2006· article· en· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Prevention
2014· book-chapter· en· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Prevention
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Traffic law enforcement and safety
Donald A. Redelmeier, Robert Tibshirani, Leonard Evans
2003· article· en· The Lancet· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Preface
Anne Andermann
2012· book-chapter· en· Cambridge University Press eBooks· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About