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
Primary Care and Health Outcomes
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.

4,685 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.
4,685 works in the cohort · of 4,299,418page 23 of 94

Labels cover 32 of 4,685 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 4,685 of 4,685 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.

affno abstractunlabeled
Implementation and trial evidence: a plea for fore-thought
Paul Brocklehurst, Lynne Williams, Christopher R Burton, Travis R. Goodwin, Jo Rycroft‐Malone
2017· article· en· BDJ· Health Professions
machine prediction:candidate · metaresearchconsensus · metaresearch
10
citations
venueaboutno affunlabeled
Record number of unmatched medical graduates
Lauren Vogel
2017· article· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
10
citations
fundno affunlabeled
Academic psychiatry is everyone's business
Hugo Critchley, Derek K. Tracy, Gin S. Malhi, Laith Alexander, David S. Baldwin, Jonathan Cavanagh +23 more
2024· editorial· en· The British Journal of Psychiatry· Health Professions
machine prediction:candidate · noneconsensus · none
10
citations
affvenueunlabeled
The past and future of the generalist general surgeon
Eric M. Webber, Vivian C. McAlister, Lisa Gorman, Sarah Taber, Kenneth D. Harris
2014· article· en· Canadian Journal of Surgery· Health Professions
machine prediction:candidate · noneconsensus · none
10
citations
affvenueaboutunlabeled
Strategizing Research for Impact
Denis Roy, Matthew Menear, Hassane Alami, Jean‐Louis Denis
2022· review· en· A Nudge Too Far? A Nudge at All? On Paying People to Be Healthy· Health Professions
machine prediction:candidate · metaresearchconsensus · none
10
citations
affvenueno abstractunlabeled
Family physicians as generalists
Margaret Tromp
2019· editorial· en· Canadian Journal of Rural Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
10
citations
aboutno affunlabeled
Preventive Medicine 2000
Alicia M. McClary, Paul R. Marantz, Margaret H. Taylor
2000· article· en· Academic Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
10
citations
aboutno affno abstractunlabeled
Who are the high hospital users? A Canadian case study
Noralou P. Roos, Charles Burchill, Keumhee C. Carrière
2003· article· en· Journal of Health Services Research & Policy· Health Professions
machine prediction:candidate · noneconsensus · none
10
citations
venueno affunlabeled
What makes a good medical journal great?
Bartosz Hudzik
2016· letter· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · metaresearchconsensus · none
10
citations

How this was built: Screen · Findings · About