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
Health and Medical Education
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.

235 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.
235 works in the cohort · of 4,299,418page 4 of 5

Labels cover 4 of 235 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 235 of 235 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.

fundno affunlabeled
Publica tu investigación con Elsevier
Anthony Newman, Massimiliano Bearzot
2015· article· es· RiuNet (Politechnical University of Valencia)· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Prevalencia de maloclusiones en la dentición primaria
Olga Raquel Zambrano de Ceballos, Yanira Añez, Luis Eduardo Rivera Velázquez, Juan A. Oliveira del Río, Judith Socorro Villalobos de García
2014· article· es· Ciencia Odontológica· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Calidad de la atención médica en consultorio selecionado
Omar Medardo Martín Sánchez, María Teresa Chávez Reyes, Emilia Conill Linares, Juan Luis García Naranjo
2017· article· es· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Editorial
José I. Rojas‐Méndez
2020· editorial· es· Multidisciplinary Business Review· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
New directions for the Revista/Journal
María Luisa Clark
2001· article· en· Revista Panamericana de Salud Pública· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0186-0216(09)89015-0
2000· book-chapter· en· Time to knit· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Un sueño realizado
Rafael Ángel García Portela
2016· article· es· Revista de Ciencias Médicas de Pinar del Río· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
ÁNGELES BARRAZA, RUMBO A LA OLIMPIADA
Ángeles Barraza
2002· article· es· Gaceta UNAM (2000-2009)· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About