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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 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 22 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 affno abstractunlabeled
Cell death assays for drug discovery
Oliver Kepp, Lorenzo Galluzzi, Marta M. Lipinski, Junying Yuan, Guido Kroemer
2011· review· en· Nature Reviews Drug Discovery· Medicine
machine prediction:candidate · noneconsensus · none
554
citations
fundno affno abstractunlabeled
Comparison of Cas9 activators in multiple species
Alejandro Chavez, Marcelle Tuttle, Benjamin W. Pruitt, Ben Ewen‐Campen, Raj Chari, Dmitry Ter‐Ovanesyan +8 more
2016· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
553
citations
fundno affunlabeled
Reelin promoter hypermethylation in schizophrenia
Dennis R. Grayson, Xiaomei Jia, Ying Chen, Rajiv P. Sharma, Colin Mitchell, Alessandro Guidotti +1 more
2005· article· en· Proceedings of the National Academy of Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
552
citations
fundno affunlabeled
Out-group animosity drives engagement on social media
Steve Rathje, Jay Joseph Van Bavel, Sander van der Linden
2021· article· en· Proceedings of the National Academy of Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
549
citations
fundno affno abstractunlabeled
Why must T cells be cross-reactive?
Andrew K. Sewell
2012· review· en· Nature reviews. Immunology· Immunology and Microbiology
machine prediction:candidate · noneconsensus · none
547
citations
fundno affunlabeled
Sarcoma classification by DNA methylation profiling
Christian Koelsche, Daniel Schrimpf, Damian Stichel, Martin Sill, Felix Sahm, David Reuß +104 more
2021· article· en· Nature Communications· Medicine
machine prediction:candidate · noneconsensus · none
547
citations

How this was built: Screen · Findings · About