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
Clinical practice guidelines implementation
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.

2,993 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.
2,993 works in the cohort · of 4,299,418page 32 of 60

Labels cover 42 of 2,993 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 2,993 of 2,993 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.

affunlabeled
Educating Case Managers
Charlotte Sortedahl
2016· article· en· Professional Case Management· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affaboutunlabeled
Data Linkage for Optimizing Rectal Cancer Care in Alberta
Quynh Lê, Lorraine Shack, Adam Elwi, Francesca Coutinho, Ryan Rochon, Todd McMullen +1 more
2018· article· en· International Journal for Population Data Science· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Rebuttal From Dr. Guyatt et al
Gordon Guyatt, Paul J. Karanicolas, Regina Kunz
2008· article· en· CHEST Journal· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affvenueaboutunlabeled
Report Card Time for Canadian Journal of Diabetes
Heather Dean, Fiona Hendry
2007· article· en· Canadian Journal of Diabetes· Medicine
machine prediction:candidate · metaresearch+insufficient_payloadconsensus · none
1
citations
affunlabeled
Physiopy Community Practices
2024· article· en· Zenodo (CERN European Organization for Nuclear Research)· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
When 2 Guidelines Collide …
Jeffrey Johnson
2009· article· fr· Canadian Pharmacists Journal / Revue des Pharmaciens du Canada· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
NHG-Standaard Psoriasis (derde herziening)
P. G. Van Peet, Phyllis I. Spuls, J. W. Ek, H. Lantinga, L.L.A. Lecluse, A. J. Oosting +5 more
2014· article· nl· Data Archiving and Networked Services (DANS)· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
CAG News page
Derek McKay, Richard N. Fedorak
2014· article· en· Canadian Journal of Gastroenterology and Hepatology· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
1
citations

How this was built: Screen · Findings · About