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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 487 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
Does This Patient Have Delirium?
Camilla L. Wong, Jayna Holroyd‐Leduc, David L. Simel, Sharon E. Straus
2010· review· en· JAMA· Medicine
machine prediction:candidate · noneconsensus · none
432
citations
fundno affunlabeled
Global Mental Health
Vikram Patel, Martin Prince
2010· article· id· JAMA· Psychology
machine prediction:candidate · noneconsensus · none
432
citations
affunlabeled
Update on tumor-infiltrating lymphocytes (TILs) in breast cancer, including recommendations to assess TILs in residual disease after neoadjuvant therapy and in carcinoma in situ: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer
Maria Vittoria Dieci, Nina Radosevic‐Robin, Susan Fineberg, Gert Van den Eynden, Nils Ternès, Frédérique Penault‐Llorca +22 more
2017· review· en· Seminars in Cancer Biology· Medicine
machine prediction:candidate · noneconsensus · none
432
citations
affno abstractunlabeled
Global guideline for the diagnosis and management of rare mould infections: an initiative of the European Confederation of Medical Mycology in cooperation with the International Society for Human and Animal Mycology and the American Society for Microbiology
Martin Hoenigl, Jon Salmanton‐García, Thomas J. Walsh, Márcio Nucci, Chin Fen Neoh, Jeffrey D. Jenks +38 more
2021· review· en· The Lancet Infectious Diseases· Medicine
machine prediction:candidate · noneconsensus · none
432
citations
affaboutunlabeled
Pure Red-Cell Aplasia and Epoetin Therapy
Charles L. Bennett, Stefano Luminari, Allen R. Nissenson, Martin S. Tallman, Stephen A. Klinge, Norene McWilliams +12 more
2004· article· en· New England Journal of Medicine· Immunology and Microbiology
machine prediction:candidate · noneconsensus · none
432
citations
afffundunlabeled
Review of the current state of whole slide imaging in pathology
Liron Pantanowitz, Paul N. Valenstein, Andrew Evans, Keith J. Kaplan, John D. Pfeifer, David C. Wilbur +2 more
2011· article· en· Journal of Pathology Informatics· Computer Science
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

How this was built: Screen · Findings · About