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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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JMIR Medical Informatics
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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.

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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.

1,809 results · 1 filter active ·
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20022025
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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.
1,809 works in the cohort · of 4,299,418page 35 of 37

Labels cover 15 of 1,809 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 1,809 of 1,809 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.

venueno affno abstractunlabeled
Test Ltp (Preprint)
Subhashree Biswal, Tadele Abraham
2024· article· en· JMIR Medical Informatics· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affno abstractunlabeled
Real World Imaging Data: Opportunities and Challenges (Preprint)
Jie Wu, Aline Lütz de Araújo, Sean Khozin, Merel Huisman, Domenico Mastrodicasa, Martin J. Willemink
2025· article· en· JMIR Medical Informatics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Correction: Identifying Patients Who Meet Criteria for Genetic Testing of Hereditary Cancers Based on Structured and Unstructured Family Health History Data in the Electronic Health Record: Natural Language Processing Approach
Jianlin Shi, Keaton Morgan, Richard L. Bradshaw, Se-Hee Jung, Wendy Kohlmann, Kimberly A. Kaphingst +2 more
2022· erratum· en· JMIR Medical Informatics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About