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
Cerebrovascular and Carotid Artery Diseases
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.

2,192 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.
2,192 works in the cohort · of 4,299,418page 22 of 44

Labels cover 6 of 2,192 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 2,192 of 2,192 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/j.ysur.2015.10.005
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
2
citations
affunlabeled
Pre-procedural Patient Preparation
Adil Al-Riyami, Jacqueline Saw
2009· book-chapter· en· Contemporary cardiology· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
afffundno abstractunlabeled
Brain PET and Cerebrovascular Disease
Katarina Chiam, Louis Lee, Phillip H. Kuo, Vincent Gaudet, Sandra E. Black, Katherine Zukotynski
2022· review· en· PET Clinics· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Cerebrovascular disease
Ian A. Herrick
2003· article· en· Current Opinion in Anaesthesiology· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affvenueunlabeled
Cardioembolic Free-Floating Thrombus in the Common Carotid Artery
Ryan Gotfrit, Ronda Lun, Seyed‐Mohammad Fereshtehnejad, Michel Shamy
2022· article· en· Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
Bypassing Trouble
Louis R. Caplan
2012· letter· en· Archives of Neurology· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Adding Insight to Injury!
A. Ross Naylor, J. David Spence
2019· letter· en· European Journal of Vascular and Endovascular Surgery· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affvenueunlabeled
Cardioembolism: A Rare Cause of Jaw Claudication
Daniela Toffoli, Stanley Élysée, Manuel José Selva Dominguez, Sylvain Lanthier
2007· letter· en· Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques· Medicine
machine prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About