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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 1,441 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.

afffundunlabeled
TFCat: the curated catalog of mouse and human transcription factors
Debra L. Fulton, Saravanan Sundararajan, Gwenaël Badis, Timothy R. Hughes, Wyeth W. Wasserman, Jared C. Roach +1 more
2009· article· en· Genome biology· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
213
citations
affunlabeled
Quantum speed-up for unsupervised learning
Esma Aı̈meur, Gilles Brassard, Sébastien Gambs
2012· article· en· Machine Learning· Computer Science
machine prediction:candidate · noneconsensus · none
213
citations
venueaboutno affunlabeled
A lightning fire occurrence model for Ontario
B. Mike Wotton, David L. Martell
2005· article· en· Canadian Journal of Forest Research· Environmental Science
machine prediction:candidate · noneconsensus · none
213
citations
afffundno abstractunlabeled
ASlib: A benchmark library for algorithm selection
Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette +5 more
2016· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
213
citations
affunlabeled
The Effects of Musical Training on Structural Brain Development
Krista L. Hyde, Jason P. Lerch, Andrea Norton, Marie Forgeard, Ellen Winner, Alan C. Evans +1 more
2009· article· en· Annals of the New York Academy of Sciences· Neuroscience
machine prediction:candidate · noneconsensus · none
213
citations
afffundunlabeled
A comprehensive genomic history of extinct and living elephants
Eleftheria Palkopoulou, Mark Lipson, Swapan Mallick, Svend Vendelbo Nielsen, Nadin Rohland, Sina Baleka +31 more
2018· article· en· Proceedings of the National Academy of Sciences· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
213
citations

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