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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.

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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
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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 ·
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20002025
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Machine labels · sparse coverage
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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 1,222 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.

venueno affunlabeled
Virtual Reality in Medical Students’ Education: Scoping Review
Haowen Jiang, Sunitha Vimalesvaran, Jeremy King Wang, Kee Boon Lim, Sreenivasulu Reddy Mogali, Lorainne Tudor Car
2021· article· en· JMIR Medical Education· Engineering
machine prediction:candidate · noneconsensus · none
238
citations
affunlabeled
The Hanabi challenge: A new frontier for AI research
Nolan Bard, Jakob Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, Hai-Jing Song +9 more
2019· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
237
citations
affno abstractunlabeled
Recycling indium from waste LCDs: A review
Kaihua Zhang, Yufeng Wu, Wei Wang, Bin Li, Yinan Zhang, Tieyong Zuo
2015· review· en· Resources Conservation and Recycling· Environmental Science
machine prediction:candidate · noneconsensus · none
237
citations
affno abstractunlabeled
Narrative Inquiry as Pedagogy in Education
Janice Huber, Vera Caine, Marilyn Huber, Pam Steeves
2013· article· en· Review of Research in Education· Social Sciences
machine prediction:candidate · noneconsensus · none
237
citations
affunlabeled
The Perils of Unearned Income
Alastair Smith
2008· article· en· The Journal of Politics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
237
citations
afffundno abstractunlabeled
Zinc in Depression: A Meta-Analysis
Walter Swardfager, Nathan Herrmann, Graham Mazereeuw, Kyle Goldberger, Tetsuhiro Harimoto, Krista L. Lanctôt
2013· review· en· Biological Psychiatry· Nursing
machine prediction:candidate · metaepi_broadconsensus · none
237
citations
afffundno abstractunlabeled
Robust Rician noise estimation for MR images
Pierrick Coupé, José V. Manjón, Elias Gedamu, Douglas L. Arnold, Montserrat Robles, D. Louis Collins
2010· article· en· Medical Image Analysis· Computer Science
machine prediction:candidate · noneconsensus · none
237
citations
affno abstractunlabeled
An action agenda for HIV and sex workers
Chris Beyrer, Anna-Louise Crago, Linda‐Gail Bekker, Jenny Butler, Kate Shannon, Deanna Kerrigan +11 more
2014· review· en· The Lancet· Social Sciences
machine prediction:candidate · noneconsensus · none
237
citations

How this was built: Screen · Findings · About