MétaCan
Menu
Cohort builder

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.

Search term
Author
Year range
Sort
Language
Type
Field
Venue
Topic
Healthcare Systems and Practices
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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.

3,912 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
3,912 works in the cohort · of 4,299,418page 15 of 79

Labels cover 15 of 3,912 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 3,912 of 3,912 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
Médias, médicaments et espace public
Christine Thoër, Bertrand Lebouché, Joseph J. Lévy, Vittorio A. sironi
2009· book· fr· Presses de l'Université du Québec eBooks· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Promesses de l’IA en santé - Fiche 2
Aude Motulsky, Jean Noël Nikiema, Philippe Després, Alexandre Castonguay, Martin Cousineau, Joé T. Martineau +2 more
2022· report· fr· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
De travers dans la gorge
Antoine Gauthier
2021· article· fr· Critical Studies in Improvisation / Études critiques en improvisation· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Broken to the Hope
Stephen L. Mikochik
2017· article· en· The National Catholic Bioethics Quarterly· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
France
2006· book-chapter· en· OECD economic outlook· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
La formation des élites francophones
Bernard Cerquiglini
2010· article· fr· Géoéconomie/Géoéconomie· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
venueaboutno affunlabeled
Lobbying and the Public Interest
André Côté
2006· article· en· Canadian parliamentary review· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affvenueunlabeled
La logistique au cœur de la performance
Martin Beaulieu, Jean-François Venne
2018· article· fr· Gestion· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
Introduction au dossier thématique
Jaeho Eun, Pierre-Charles Pupion
2019· article· fr· Management international· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About