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
Diagnosis and Treatment of Venous 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.

403 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.
403 works in the cohort · of 4,299,418page 8 of 9

Labels cover 1 of 403 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 403 of 403 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/s2211-0364(19)30070-6
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affunlabeled
Approach to pelvic venous disorders
Andrew D Brown
2025· article· en· Canadian Family Physician· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
The Impact of Multiparity on Venous Insufficiency
Olga Bakayev, Emilia Kalutskaya, Crystal McLeod, Natalie Marks, Enrico Ascher, Anil Hingorani
2025· article· en· Journal of Vascular Surgery· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
The Impact of Multiparity on Venous Insufficiency
Olga Bakayev, Emilia Kalutskaya, Crystal McLeod, Rianna Segal, Natalie Marks, Enrico Ascher +1 more
2025· article· en· Journal of Vascular Surgery Venous and Lymphatic Disorders· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Approche des troubles veineux pelviens
Andrew D Brown
2025· article· en· Canadian Family Physician· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
VARICOSE ULCER
HENRY C.G. SEMON
2013· book-chapter· en· Elsevier eBooks· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/j.yvas.2015.06.174
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0292-062x(10)48066-6
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/b978-1-4557-0984-7.00288-x
2000· book-chapter· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s1544-8800(06)70976-9
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s2211-0364(19)78955-9
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/j.yvas.2013.04.070
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s1558-0164(10)70265-0
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/j.yvas.2015.06.177
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/j.yvas.2015.06.101
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/b978-2-294-76306-9.50583-4
2000· book-chapter· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0029-7437(05)71240-4
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/b978-0-7020-7455-4.00154-0
2000· book-chapter· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
WHSA UBUNTU Conference Report
Liezl Naudé
2010· article· en· Wound healing· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations

How this was built: Screen · Findings · About