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 · 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.
4,299,418 works in the cohort · of 4,299,418page 254 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.

afffundunlabeled
flowCore: a Bioconductor package for high throughput flow cytometry
Florian Hahne, Nolwenn Le Meur, Ryan R. Brinkman, Byron Ellis, Perry Haaland, Deepayan Sarkar +3 more
2009· article· en· BMC Bioinformatics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
651
citations
afffundno abstractunlabeled
Anti-apoptosis and cell survival: A review
Liam Portt, Grant Norman, Caitlin Clapp, Matthew Greenwood
2010· review· en· Biochimica et Biophysica Acta (BBA) - Molecular Cell Research· Medicine
machine prediction:candidate · noneconsensus · none
651
citations
affunlabeled
Human prostate cancer risk factors
David G. Bostwick, Harry Burke, Daniel Djakiew, Susan Y. Euling, Shuk‐Mei Ho, Joseph R. Landolph +5 more
2004· review· en· Cancer· Medicine
machine prediction:candidate · noneconsensus · none
650
citations
afffundno abstractunlabeled
Heat shock protein genes and their functional significance in fish
Niladri Basu, Anne E. Todgham, Paige A. Ackerman, M.R. Bibeau, Kazumi Nakano, Patricia M. Schulte +1 more
2002· review· en· Gene· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
650
citations
affno abstractunlabeled
CAD-RADSTM Coronary Artery Disease – Reporting and Data System. An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Radiology (ACR) and the North American Society for Cardiovascular Imaging (NASCI). Endorsed by the American College of Cardiology
Ricardo C. Cury, Suhny Abbara, Stephan Achenbach, Arthur Agatston, Daniel S. Berman, Matthew J. Budoff +11 more
2016· article· en· Journal of cardiovascular computed tomography· Medicine
machine prediction:candidate · metaresearchconsensus · none
650
citations
afffundno abstractunlabeled
Aging, frailty and age-related diseases
Tamàs Fülöp, Anis Larbi, Jacek M. Witkowski, Janet E. McElhaney, Mark Loeb, Arnold Mitnitski +1 more
2010· review· en· Biogerontology· Medicine
machine prediction:candidate · noneconsensus · none
650
citations
fundno affunlabeled
Activation of p53 by MEG3 Non-coding RNA
Yunli Zhou, Ying Zhong, Yingying Wang, Xun Zhang, Dalia L. Batista, Roger Gejman +4 more
2007· article· en· Journal of Biological Chemistry· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
650
citations
affunlabeled
Media Bias and Reputation
Matthew Gentzkow, Jesse M. Shapiro
2005· report· en· National Bureau of Economic Research· Social Sciences
machine prediction:candidate · noneconsensus · none
650
citations
affno abstractunlabeled
Biocatalysis
Elizabeth L. Bell, William Finnigan, Scott P. France, Anthony P. Green, Martin A. Hayes, Lorna J. Hepworth +7 more
2021· article· en· Nature Reviews Methods Primers· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
650
citations
affno abstractunlabeled
A survey on machine learning for data fusion
Tong Meng, Xuyang Jing, Zheng Yan, Witold Pedrycz
2019· article· en· Information Fusion· Computer Science
machine prediction:candidate · noneconsensus · none
650
citations
affno abstractunlabeled
Environmental performance of blue foods
Jessica A. Gephart, Patrik J. G. Henriksson, Robert Parker, Alon Shepon, Kelvin D. Gorospe, Kristina Bergman +12 more
2021· article· en· Nature· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
650
citations
fundno affunlabeled
Where ethics and politics meet
Miriam Ticktin
2006· article· en· American Ethnologist· Psychology
machine prediction:candidate · noneconsensus · none
649
citations

How this was built: Screen · Findings · About