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
Journal of Clinical Epidemiology
Topic
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.

1,510 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.
1,510 works in the cohort · of 4,299,418page 10 of 31

Labels cover 96 of 1,510 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 1,510 of 1,510 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
Modified intention-to-treat analysis did not bias trial results
Anna Døssing, Simon Tarp, Daniel E. Furst, Christian Gluud, George A. Wells, Joseph Beyene +3 more
2015· review· en· Journal of Clinical Epidemiology· Medicine
machine prediction:candidate · metaresearchconsensus · none
54
citations
afffundno abstractunlabeled
Modelling time-dependent hazard ratios in relative survival
Philippe Bolard, Catherine Quantin, Jacques Estève, Jean Faivre, Michał Abrahamowicz
2001· article· en· Journal of Clinical Epidemiology· Medicine
machine prediction:candidate · noneconsensus · none
52
citations
affno abstractunlabeled
What kind of randomized trials do we need?
Merrick Zwarenstein, Shaun Treweek
2009· article· en· Journal of Clinical Epidemiology· Medicine
machine prediction:candidate · metaresearchconsensus · metaresearch
52
citations
affno abstractunlabeled
The randomized placebo-phase design for clinical trials
Brian M. Feldman, Elaine Wang, Andrew R. Willan, John Paul Szalai
2001· article· en· Journal of Clinical Epidemiology· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
51
citations
afffundno abstractunlabeled
Reporting the study populations of clinical trials
Stanley H. Shapiro, Charles Weijer, Benjamin Freedman
2000· article· en· Journal of Clinical Epidemiology· Decision Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
50
citations
affno abstractunlabeled
Discrepancies among megatrials
Toshi A. Furukawa, David L. Streiner, Shiro Hori
2000· article· en· Journal of Clinical Epidemiology· Social Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
49
citations

How this was built: Screen · Findings · About