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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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Interpreting and Communication in Healthcare
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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.

1,286 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.
1,286 works in the cohort · of 4,299,418page 14 of 26

Labels cover 4 of 1,286 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 1,286 of 1,286 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.

fundvenueno affno abstractunlabeled
Writing the lay summary: basics
Heidi Cramm, Janet Breimer, Lydia Lee, Julie Burch, Valerie Ashford
2017· article· en· Journal of Military Veteran and Family Health· Health Professions
machine prediction:candidate · metaresearchconsensus · none
2
citations
affunlabeled
Working Memory and Interpreting Studies
Binghan Zheng, Huolingxiao Kuang
2022· book-chapter· en· Cambridge University Press eBooks· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Cautious Curiosity
Amolpreet Toor
2021· article· en· The AMA Journal of Ethic· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Health care across a language divide
Ellen Rosenberg
2010· letter· en· Patient Education and Counseling· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affvenueunlabeled
Améliorer le dépistage chez les patients autochtones
Pascale Breault, Jessie Nault, Michèle Audette, Sandro Échaquan, Jolianne Ottawa, Olga Szafran +6 more
2021· article· fr· Canadian Family Physician· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About