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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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Digital Imaging for Blood Diseases
Retraction
Abstract
Evidence source
Study design
Label agreement
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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
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

241 results · 1 filter active ·
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20032025
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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.
241 works in the cohort · of 4,299,418page 4 of 5

Labels cover 1 of 241 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 241 of 241 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.

aboutno affunlabeled
Rugby -- Australian Wallabies, 1958
2021· dataset· en· University of Southern California Digital Library· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Needs of palliative care in people with dementia
2017· dissertation· pt· Repositório Comum (Repositório Científico de Acesso Aberto de Portugal)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Imagma Dataset
Viranga Perera, Alan P. Jackson
2018· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
OConnor-Lab-UBC/BEF_scaling_LV: updated to revision
Patrick L. Thompson, Joey R. Bernhardt
2020· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
ROC
University Research Chair
2009· book-chapter· en· Encyclopedia of Database Systems· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Pushing the Limits of Learning from Limited Data
Maya Malaviya, Ilia Sucholutsky, Thomas L. Griffiths
2024· article· en· Proceedings of the AAAI Symposium Series· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
The fractal geometry of blood clots
Joshua Thon, Elizabeth Keys, Hannah Park, Emily Been
2011· article· en· Canadian acoustics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About