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 cost, quality, 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.

1,204 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.
1,204 works in the cohort · of 4,299,418page 6 of 25

Labels cover 31 of 1,204 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 1,204 of 1,204 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
The future of quality improvement research
Rebecca S. Miltner, Jeremiah H Newsom, Brian S. Mittman
2013· article· en· Implementation Science· Health Professions
machine prediction:candidate · metaresearchconsensus · none
12
citations
affno abstractunlabeled
Wish-fulfilling medicine and wish-fulfilling dentistry
D.J. Witter, J.J. Kole, W. Brands, Michael I. MacEntee, N.H.J. Creugers
2020· review· en· Journal of Dentistry· Health Professions
machine prediction:candidate · noneconsensus · none
11
citations
affvenueunlabeled
Critical Care Strategic Clinical Network
Samantha L. Bowker, Henry T. Stelfox, Sean M. Bagshaw
2019· article· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
11
citations
affaboutunlabeled
Innovation in the Canadian health system
Tom Noseworthy
2020· article· en· Healthcare Management Forum· Health Professions
machine prediction:candidate · noneconsensus · none
10
citations
affunlabeled
Time to move forward
Charles Tomson, E. J. Lamb, K. Griffith, Donal O’Donoghue, John Feehally
2007· letter· en· BMJ· Health Professions
machine prediction:candidate · noneconsensus · none
10
citations
affunlabeled
Virtue, progress and practice
Michael Loughlin, Robyn Bluhm, Stephen Buetow, Ross Upshur, Maya J. Goldenberg, Kirstin Borgerson +1 more
2011· editorial· en· Journal of Evaluation in Clinical Practice· Health Professions
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractgemma · metaresearchgpt · no categorymodels split
Towards scientific medicine: an information‐age outlook
Olli S. Miettinen, Lucas M. Bachmann, Johann Steurer
2008· review· en· Journal of Evaluation in Clinical Practice· Health Professions
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
Theranos revisited: the trial and lessons learned
Eleftherios P. Diamandis, Karl J. Lackner, Mario Plebani
2021· letter· en· Clinical Chemistry and Laboratory Medicine (CCLM)· Health Professions
machine prediction:candidate · research_integrityconsensus · none
9
citations
affaboutno abstractunlabeled
Choosing Wisely Canada: scratching the 7-year itch
Kuan-chin Jean Chen, Venkatesh Thiruganasambandamoorthy, Samuel Campbell, Suneel Upadhye, Shawn Dowling, Lucas B. Chartier
2022· editorial· en· Canadian Journal of Emergency Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
9
citations

How this was built: Screen · Findings · About