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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.

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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 · 0 filters active
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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 915 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
You Watch, You Give, and You Engage
Zhicong Lu, Haijun Xia, Seongkook Heo, Daniel Wigdor
2018· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
288
citations
aboutno affunlabeled
Mental health in the Americas: an overview of the treatment gap
Robert Kohn, Ali Ahsan Ali, Victor Puac‐Polanco, Chantal Figueroa, Victor López-Soto, Kristen E. Morgan +2 more
2018· article· es· Revista Panamericana de Salud Pública· Psychology
machine prediction:candidate · noneconsensus · none
287
citations
afffundunlabeled
Learning deep physiological models of affect
Héctor P. Martínez, Yoshua Bengio, Georgios N. Yannakakis
2013· article· en· IEEE Computational Intelligence Magazine· Psychology
machine prediction:candidate · noneconsensus · none
287
citations
afffundno abstractunlabeled
Increasing the flow of carbon into seed oil
Randall J. Weselake, David C. Taylor, Mukhlesur Rahman, Saleh Shah, André Laroche, P. B. E. McVetty +1 more
2009· review· en· Biotechnology Advances· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
287
citations
affaboutunlabeled
Adult Intussusception: A Retrospective Review
Ahmad Zubaidi, Faisal Alsaif, Richard Silverman
2006· review· en· Diseases of the Colon & Rectum· Medicine
machine prediction:candidate · noneconsensus · none
287
citations
affunlabeled
The Vanishing Nonforensic Autopsy
Kaveh G Shojania, Elizabeth C. Burton
2008· article· en· New England Journal of Medicine· Medicine
machine prediction:candidate · noneconsensus · none
287
citations
affno abstractunlabeled
Why conservation biology can benefit from sensory ecology
Davide M. Dominoni, Wouter Halfwerk, Emily Baird, Rachel T. Buxton, Esteban Fernández‐Juricic, Kurt M. Fristrup +12 more
2020· review· en· Nature Ecology & Evolution· Environmental Science
machine prediction:candidate · noneconsensus · none
287
citations
affno abstractunlabeled
Alopecia areata update
Abdullah Alkhalifah, Adel Alsantali, Eddy Wang, Kevin J. McElwee, Jerry Shapiro
2010· review· en· Journal of the American Academy of Dermatology· Medicine
machine prediction:candidate · noneconsensus · none
287
citations
affno abstractunlabeled
Cognitive approaches to emotions
Keith Oatley, P. N. Johnson‐Laird
2014· review· en· Trends in Cognitive Sciences· Neuroscience
machine prediction:candidate · noneconsensus · none
287
citations

How this was built: Screen · Findings · About