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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.

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This cohort has 196,966 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.

196,966 results · 2 filters 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.
196,966 works in the cohort · of 4,299,418page 32 of 3,940

Labels cover 472 of 196,966 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 196,966 of 196,966 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.

fundno affunlabeled
Bromodomains as therapeutic targets
Susanne Müller, P. Filippakopoulos, Stefan Knapp
2011· review· en· Expert Reviews in Molecular Medicine· Medicine
machine prediction:candidate · noneconsensus · none
436
citations
fundno affno abstractunlabeled
Target validation using chemical probes
Mark E. Bunnage, Eugene L. Piatnitski Chekler, Lyn H. Jones
2013· article· en· Nature Chemical Biology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
435
citations
fundno affunlabeled
Modeling Consumer Demand for Variety
Jaehwan Kim, Greg M. Allenby, Peter E. Rossi
2002· article· en· Marketing Science· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
434
citations
fundno affunlabeled
Global Mental Health
Vikram Patel, Martin Prince
2010· article· id· JAMA· Psychology
machine prediction:candidate · noneconsensus · none
432
citations
fundno affno abstractunlabeled
Safety Update
Michael J. Joyner, Katelyn A. Bruno, Stephen A. Klassen, Katie L. Kunze, Patrick W. Johnson, Elizabeth R. Lesser +34 more
2020· article· es· Mayo Clinic Proceedings· Medicine
machine prediction:candidate · noneconsensus · none
432
citations
fundno affno abstractunlabeled
Microbiome-based therapeutics
Matthew T. Sorbara, Eric G. Pamer
2022· review· en· Nature Reviews Microbiology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
432
citations
fundno affunlabeled
Developmental origins of metabolic diseases
Daniël J. Hoffman, Theresa L. Powell, Emily S. Barrett, Daniel B. Hardy
2020· review· en· Physiological Reviews· Medicine
machine prediction:candidate · noneconsensus · none
431
citations
fundno affunlabeled
Psychological therapies for people with borderline personality disorder
Ole Jakob Storebø, Jutta Stoffers‐Winterling, Birgit Vӧllm, Mickey Kongerslev, Jessica T. Mattivi, Mie Sedoc Jørgensen +6 more
2020· review· en· Cochrane Database of Systematic Reviews· Psychology
machine prediction:candidate · noneconsensus · none
431
citations
fundno affunlabeled
The Neural Autoregressive Distribution Estimator
Hugo Larochelle, Iain Murray
2011· article· en· Edinburgh Research Explorer (University of Edinburgh)· Computer Science
machine prediction:candidate · noneconsensus · none
431
citations
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