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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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BMJ evidence-based medicine
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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.

125 results · 1 filter active ·
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20182025
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Categories
Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
125 works in the cohort · of 4,299,418page 2 of 3

Labels cover 115 of 125 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 125 of 125 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 abstractgemma · metaresearchgpt · no categorymodels split
Understanding synthetic data: artificial datasets for real-world evidence
Randi E. Foraker, Jon D. Morrow, Julie A. Johnson, Adam Wilcox, Alan J. Forster, Philip Payne
2025· article· en· BMJ evidence-based medicine· Computer Science
machine prediction:candidate · metaresearchconsensus · none
7
citations
affgemma · no categorygpt · no categorymodels agree
Drug discovery today: no molecules required
Alexander Y. Panchin, Н. Н. Хромов-Борисов, Evgenia V. Dueva
2018· article· en· BMJ evidence-based medicine· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractgemma · metaresearchgpt · metaresearchmodels split
Challenges in the selection and measurement of outcomes in psychiatric trials
Sophie Juul, Pascal Faltermeier, Faiza Siddiqui, Johanne Juul Petersen, Caroline Barkholt Kamp, Rikke Hermann Jakobsen +9 more
2025· article· en· BMJ evidence-based medicine· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
6
citations
affno abstractgemma · no categorygpt · no categorymodels agree
Choosing wisely 10 years later: reflection and looking ahead
Moriah Ellen, Luís Cláudio Lemos Correia, Wendy Levinson
2023· article· en· BMJ evidence-based medicine· Health Professions
machine prediction:candidate · noneconsensus · none
4
citations
affgemma · no categorygpt · no categorymodels agree
Partnering with patients in the production of evidence
Peter J. Gill, Emma Cartwright
2020· letter· en· BMJ evidence-based medicine· Health Professions
machine prediction:candidate · metaresearchconsensus · metaresearch
4
citations
affno abstractgemma · metaresearchgpt · no categorymodels split
Exploring advanced methods for network meta-analysis
Areti Angeliki Veroniki, Juan Víctor Ariel Franco
2023· editorial· en· BMJ evidence-based medicine· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
3
citations
affno abstractgemma · stsgpt · no categorymodels split
The path of Chile towards the institutionalisation of evidence-based health policy
Paula García-Celedón, Deborah Navarro-Rosenblatt, Carolina Ibarra-Castillo, Lucy Kuhn-Barrientos, Cristián Mansilla, Dino Sepúlveda
2025· article· en· BMJ evidence-based medicine· Health Professions
machine prediction:candidate · metaresearchconsensus · none
2
citations
affgemma · metaresearch+bibliometricsgpt · metaresearchmodels split
Over 1000 terms have been used to describe evidence synthesis: a scoping review
Danielle Pollock, Sabira Hasanoff, Timothy Hugh Barker, Barbara Clyne, Andrea C. Tricco, Andrew Booth +33 more
2025· review· en· BMJ evidence-based medicine· Decision Sciences
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
2
citations
affno abstractgemma · metaresearchgpt · metaresearchmodels split
Proposed framework for unifying disease definitions in guideline development
Hassan Kawtharany, Muayad Azzam, M. Hassan Murad, Rebecca L. Morgan, Yngve Falck–Ytter, Shahnaz Sultan +2 more
2025· article· en· BMJ evidence-based medicine· Medicine
machine prediction:candidate · metaresearchconsensus · none
1
citations

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