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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.

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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 27 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 affunlabeled
A New Natural Language Processing–Inspired Methodology (Detection, Initial Characterization, and Semantic Characterization) to Investigate Temporal Shifts (Drifts) in Health Care Data: Quantitative Study
Bruno Barbosa Miranda de Paiva, Marcos André Gonçalves, Leonardo Rocha, Milena Soriano Marcolino, Maíra Viana Rego Souza-Silva, Jussara M. Almeida +32 more
2024· article· en· JMIR Medical Informatics· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
venueno affunlabeled
A Case Demonstration of the Open Health Natural Language Processing Toolkit From the National COVID-19 Cohort Collaborative and the Researching COVID to Enhance Recovery Programs for a Natural Language Processing System for COVID-19 or Postacute Sequelae of SARS CoV-2 Infection: Algorithm Development and Validation
Andrew Wen, Liwei Wang, Huan He, Sunyang Fu, Sijia Liu, David A. Hanauer +27 more
2024· article· en· JMIR Medical Informatics· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
venueno affgemma · no categorygpt · no categorymodels agree
Identifying and Optimizing Factors Influencing the Implementation of a Fast Healthcare Interoperability Resources Accelerator: Qualitative Study Using the Consolidated Framework for Implementation Research–Expert Recommendations for Implementing Change Approach
Jane Li, Emma Maddock, Michael Hosking, Kate Ebrill, J. Greer Sullivan, Kylynn Loi +4 more
2025· article· en· JMIR Medical Informatics· Health Professions
machine prediction:candidate · noneconsensus · none
3
citations
venueno affunlabeled
Correction: Use of an Electronic Clinical Decision Support System in Primary Care to Assess Inappropriate Polypharmacy in Young Seniors With Multimorbidity: Observational, Descriptive, Cross-Sectional Study
Eloísa Rogero-Blanco, Juan A. López-Rodríguez, Teresa Sanz‐Cuesta, Mercedes Aza‐Pascual‐Salcedo, M Jose Bujalance-Zafra, Isabel del Cura-González
2020· erratum· en· JMIR Medical Informatics· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
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