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.

This cohort has 4,299,418 works, more than the 100,000-row export cap: the file will contain the first 100,000 ordered by OpenAlex id, and says so in its last line. Narrow the cohort, page the API, or rebuild the frame from the repository for the rest. 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
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.

4,299,418 results · 0 filters 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.
4,299,418 works in the cohort · of 4,299,418page 2,604 of 85,989

Labels cover 11,048 of 4,299,418 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 4,299,418 of 4,299,418 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
Ethyl-EPA in Huntington disease
Basant K. Puri, Blair R. Leavitt, Michael R. Hayden, Christopher A. Ross, Adam Rosenblatt, J. Timothy Greenamyre +6 more
2005· article· en· Neurology· Neuroscience
machine prediction:candidate · noneconsensus · none
141
citations
affgemma · metaresearchgpt · no categorymodels split
An emerging consensus on grading recommendations?
Gordon Guyatt
2006· article· en· Evidence-Based Medicine· Medicine
machine prediction:candidate · metaresearchconsensus · metaresearch
141
citations
afffundno abstractunlabeled
NAD+ salvage pathway in cancer metabolism and therapy
Barry E. Kennedy, Tanveer Sharif, Emma Martell, Cathleen Dai, Youra Kim, Patrick W.K. Lee +1 more
2016· review· en· Pharmacological Research· Medicine
machine prediction:candidate · noneconsensus · none
141
citations
affno abstractunlabeled
Psychosocial Aspects Of Aging Skin
Madhulika A. Gupta, Barbara A. Gilchrest
2005· review· en· Dermatologic Clinics· Psychology
machine prediction:candidate · noneconsensus · none
141
citations
affno abstractunlabeled
Interpretation of radiomics features–A pictorial review
Ali Abbasian Ardakani, Nathalie J. Bureau, Edward J. Ciaccio, U. Rajendra Acharya
2021· review· en· Computer Methods and Programs in Biomedicine· Medicine
machine prediction:candidate · noneconsensus · none
141
citations
afffundno abstractunlabeled
Biaxial mechanical testing of human sclera
Armin Eilaghi, John G. Flanagan, Inka Tertinegg, Craig A. Simmons, G. Wayne Brodland, C. Ross Ethier
2010· article· en· Journal of Biomechanics· Medicine
machine prediction:candidate · noneconsensus · none
141
citations
afffundvenueaboutunlabeled
Defining priorities for improving end-of-life care in Canada
D. Heyland, Richard J. Cook, Graeme Rocker, Peter Dodek, Demetrios J. Kutsogiannis, Yoanna Skrobik +3 more
2010· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
141
citations

How this was built: Screen · Findings · About