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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.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Blood donation and transfusion practices
Retraction
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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.

affaffiliation
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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.

838 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
838 works in the cohort · of 4,299,418page 17 of 17

Labels cover 1 of 838 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 838 of 838 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.

affno abstractunlabeled
Prohibited blood donations, but not always
Juan A. Mayoral, Kerman Calvo
2016· article· es· Research at the University of Copenhagen (University of Copenhagen)· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
50 years of Vox Sanguinis International Forums
Miquel Lozano, Nancy M. Dunbar, Dana V. Devine
2020· article· en· Vox Sanguinis· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A stressful predicament for blood bankers!
Donald R. Branch
2020· letter· en· Transfusion Medicine· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Profil des donneurs de sang à l’Université de Kinshasa 2022-2024
Tshilanda Gloriane Tshibwabwa, Mvika Eddy Sokolua, Lodi Olivier Lomamba, Ndona Yvette Nuakafuti, Lalo Modeste Loseke, Ngoma Alain Mayindu +1 more
2025· article· fr· Transfusion Clinique et Biologique· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
Signes annonciateurs du décès
Heidi Marx
2024· article· fr· Canadian Medical Association Journal· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Surveillance épidémiologique des donneurs de sang à Kinshasa, 2019–2023
Lodi Olivier Lomamba, Mvika Eddy Sokolua, Mulumba Alphonsine Kamuanya, Mafuana Gina Kusundila, Manzenza Stany Lema, Lalo Modeste Loseke +1 more
2025· article· fr· Transfusion Clinique et Biologique· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About