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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.

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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
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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 5 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.

affaboutunlabeled
Public health and collaborative governance
Katherine Fierlbeck
2010· article· en· Canadian Public Administration· Health Professions
machine prediction:candidate · noneconsensus · none
17
citations
affunlabeled
Toolkit for detecting misused epidemiological methods
Colin L. Soskolne, Shira Kramer, Juan Pablo Ramos-Bonilla, Daniele Mandrioli, Jennifer Sass, Michael Gochfeld +3 more
2021· article· en· Environmental Health· Health Professions
machine prediction:candidate · metaresearchconsensus · metaresearch
16
citations
affunlabeled
Mortalidad por Cáncer en México: actualización 2015
Fernando Aldaco-Sarvide, Perla Pérez-Pérez, María G. Cervantes-Sánchez, Laura Torrecillas-Torres, Aura Argentina Erazo-Valle-Solís, Paula Cabrera‐Galeana +4 more
2018· article· es· Gaceta Mexicana de Oncología· Health Professions
machine prediction:candidate · noneconsensus · none
15
citations
aboutno affunlabeled
Public health: what is to be done?
Richard Schabas
2002· article· en· PubMed· Health Professions
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
Public Health in the Americas
Ross Duncan
2010· article· en· Italian Journal of Public Health· Health Professions
machine prediction:candidate · noneconsensus · none
14
citations
affaboutunlabeled
Criteria-Based Resource Allocation
J. Ross Graham, Christopher Mackie
2015· article· en· Journal of Public Health Management and Practice· Health Professions
machine prediction:candidate · noneconsensus · none
13
citations
aboutno affunlabeled
Canadian Health Law and Policy
Joanna N. Erdman
2017· article· en· eYLS (Yale Law School)· Health Professions
machine prediction:candidate · noneconsensus · none
13
citations

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