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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 647 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.

aboutno affunlabeled
Cohort Profile Update: The HUNT Study, Norway
Bjørn Olav Åsvold, Arnulf Langhammer, Tommy Aune Rehn, Grete Kjelvik, Trond Viggo Grøntvedt, Elin Pettersen Sørgjerd +15 more
2022· article· en· International Journal of Epidemiology· Environmental Science
machine prediction:candidate · noneconsensus · none
361
citations
fundno affno abstractunlabeled
Psoriasis: Which therapy for which patient
Shivani B. Kaushik, Mark Lebwohl
2018· review· en· Journal of the American Academy of Dermatology· Immunology and Microbiology
machine prediction:candidate · noneconsensus · none
361
citations
aboutno affunlabeled
Poststroke Dementia
Raquel Barba, Susana Martı́nez-Espinosa, Elena Rodríguez-García, Margarita Pondal, José Vivancos, Teodoro del Ser
2000· article· en· Stroke· Medicine
machine prediction:candidate · noneconsensus · none
361
citations
affunlabeled
Learning with Pseudo-Ensembles
Phil Bachman, Ouais Alsharif, Doina Precup
2014· article· en· arXiv (Cornell University)· Mathematics
machine prediction:candidate · noneconsensus · none
361
citations
afffundno abstractunlabeled
Dynamic risk analysis using bow-tie approach
Nima Khakzad, Faisal Khan, Paul Amyotte
2012· article· en· Reliability Engineering & System Safety· Decision Sciences
machine prediction:candidate · noneconsensus · none
361
citations
affunlabeled
Knowledge spillovers and the geography of innovation
David B. Audretsch, Maryann P. Feldman
2004· preprint· en· RePEc: Research Papers in Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
360
citations
affunlabeled
Action Recognition using Visual Attention
Shikhar Sharma, Ryan Kiros, Ruslan Salakhutdinov
2015· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
360
citations
afffundunlabeled
Bosonic super-WIMPs as keV-scale dark matter
Maxim Pospelov, Adam Ritz, M.B. Voloshin
2008· article· en· Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D, Particles, fields, gravitation, and cosmology· Physics and Astronomy
machine prediction:candidate · noneconsensus · none
360
citations
affno abstractunlabeled
Pathology and physiopathology of adenomyosis
Christine Bergeron, Frédéric Amant, Alex Ferenczy
2006· review· en· Best Practice & Research Clinical Obstetrics & Gynaecology· Medicine
machine prediction:candidate · noneconsensus · none
360
citations
afffundno abstractunlabeled
It's all relative: analyzing microbiome data as compositions
Gregory B. Gloor, Jia Wu, Vera Pawlowsky‐Glahn, Juan José Egozcue
2016· review· en· Annals of Epidemiology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
360
citations
afffundunlabeled
Influenza Forecasting with Google Flu Trends
Andrea Dugas, Mehdi Jalalpour, Yulia R. Gel, Scott Levin, Fred Torcaso, Takeru Igusa +1 more
2013· article· en· PLoS ONE· Medicine
machine prediction:candidate · noneconsensus · none
360
citations

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