MétaCan
ENFR
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.

Export CSVExport JSONAPI query

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
Medical Malpractice and Liability Issues
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.

1,259 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.
1,259 works in the cohort · of 4,299,418page 14 of 26

Labels cover 3 of 1,259 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 1,259 of 1,259 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.

venueno affno abstractunlabeled
10.1016/s1558-0164(06)70095-5
2000· article· en· Time to knit· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
From the Editor
Heidi M. Koenig
2020· article· en· Journal of Medical Regulation· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Physical abuse: actual physical harm
David N. Weisstub, Emilio Mordini
2001· book-chapter· en· Cambridge University Press eBooks· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Canada Thistle
2002· article· Lincoln (University of Nebraska)· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s1541-9800(11)70627-5
2000· article· en· Time to knit· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Medicolegal issues
Michel Lacerte
2002· article· en· Physical Medicine and Rehabilitation Clinics of North America· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Quebec Code of Civil Procedure
hvaillancourt
2008· article· en· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Robotic surgery in Canadian law
Bernard M. Dickens
2008· article· en· Clinical Risk· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affno abstractunlabeled
10.1016/s1541-9800(10)70171-x
2000· article· en· Time to knit· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
State and federal legislative interests
David Birnbaum, Rachel L. Stricof
2012· article· en· Clinical Governance An International Journal· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Better to mediate than litigate, MDs argue
Barbara Sibbald
2000· article· en· Europe PMC (PubMed Central)· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
What are you prepared to see?
Hugh MacLeod
2011· article· en· PubMed· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affvenueaboutunlabeled
P.009 Physician assisted death and the neurosurgeon
SP Barry, Ian Fleetwood, K. Reddy, Chris Ekong, Peter Gorman, Brian Wheelock +1 more
2016· article· en· Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
International Briefs
2010· article· en· Journal of Medical Regulation· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Canada
Richard D. Schneider, Hy Bloom
2025· book-chapter· en· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
← previousnext →

How this was built: Screen · Findings · About