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
PubMed
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.

23,401 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.
23,401 works in the cohort · of 4,299,418page 384 of 469

Labels cover 41 of 23,401 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 23,401 of 23,401 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
Six Myths About Pharmacare.
Joel Lexchin
2017· article· en· PubMed· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
[Dementia care in Germany].
M H van der Vaart
2017· article· nl· PubMed· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Taking the baton.
Obi Amadi
2010· article· en· PubMed· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
The problem with Darzi.
Alan Maynard
2009· article· en· PubMed· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Legends in urology.
Jack L. Sales
2008· article· en· PubMed· Arts and Humanities
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
[no title]
François Lespérance
2018· editorial· fr· PubMed
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
[no title]
Sylvie Rey, Philippe Voyer, Lucie Juneau
2018· article· fr· PubMed
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
[no title]
Anne‐Marie Lowe
2018· article· fr· PubMed
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
The cost of keeping non-DVM staff.
Darren Osborne
2008· article· en· PubMed· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Just a family doc.
Kuljit K. Sajjan
2001· letter· en· PubMed· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
BMA gives thumbs down to regulatory body.
Caroline Richmond
2000· article· en· PubMed· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Update on perinatal HIV.
Adriana Moldovan Costei, Susan King, Gideon Koren
2001· article· en· PubMed· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
2012 wage report for non-DVMs.
Darren Osborne
2013· article· en· PubMed· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
← previousnext →

How this was built: Screen · Findings · About