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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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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.

1,914 results · 1 filter active ·
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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.
1,914 works in the cohort · of 4,299,418page 7 of 39

Labels cover 1,914 of 1,914 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 1,914 of 1,914 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 · metaresearch+bibliometricsgpt · bibliometricsmodels split
Exploring the interdisciplinarity patterns of highly cited papers
Shiji Chen, Junping Qiu, Clément Arsenault, Vincent Larivière
2020· article· en· Journal of Informetrics· Decision Sciences
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
56
citations
afffundgemma · metaresearchgpt · metaresearch+research_integritymodels split
Rapid review method series: interim guidance for the reporting of rapid reviews
Adrienne Stevens, Mona Hersi, Chantelle Garritty, Lisa Hartling, Beverley Shea, Lesley Stewart +2 more
2024· article· en· BMJ evidence-based medicine· Decision Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
55
citations
affgemma · metaresearchgpt · metaresearchmodels agree
Assessing assumptions for statistical analyses in randomised clinical trials
Emil Eik Nielsen, Anders Kehlet Nørskov, Theis Lange, Lehana Thabane, Jørn Wetterslev, Jan Beyersmann +7 more
2019· article· en· BMJ evidence-based medicine· Decision Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
53
citations
affgemma · metaresearchgpt · metaresearchmodels agree
The rocky road: qualitative research as evidence
Mita Giacomini
2001· editorial· en· Evidence-Based Medicine· Health Professions
machine prediction:candidate · metaresearchconsensus · metaresearch
53
citations
affno abstractgemma · metaresearch+research_integritygpt · metaresearch+research_integritymodels agree
Retraction of Neurosurgical Publications: A Systematic Review
Justin Wang, Jerry C. Ku, Naif M. Alotaibi, James T. Rutka
2017· review· en· World Neurosurgery· Social Sciences
machine prediction:candidate · metaresearch+research_integrityconsensus · none
53
citations
affgemma · metaresearch+research_integritygpt · research_integrity+scholarly_communicationmodels split
‘Stamp out paper mills’ — science sleuths on how to fight fake research
Anna Abalkina, René Aquarius, Elisabeth M. Bik, David Bimler, Dorothy Bishop, Jennifer A. Byrne +4 more
2025· article· en· Nature· Social Sciences
machine prediction:candidate · metaresearch+research_integrityconsensus · none
50
citations
fundno affgemma · metaresearchgpt · no categorymodels split
Point estimation for adaptive trial designs I: A methodological review
David S. Robertson, Babak Choodari‐Oskooei, Munyaradzi Dimairo, Laura Flight, Philip Pallmann, Thomas Jaki
2022· review· en· Statistics in Medicine· Mathematics
machine prediction:candidate · metaresearchconsensus · none
49
citations
affgemma · metaresearchgpt · no categorymodels split
Merging of the National Cancer Institute–funded cooperative oncology group data with an administrative data source to develop a more effective platform for clinical trial analysis and comparative effectiveness research: a report from the Children's Oncology Group
Richard Aplenc, Brian T. Fisher, Yuanjie Huang, Yuelin Li, Todd A. Alonzo, Robert B. Gerbing +7 more
2012· article· en· Pharmacoepidemiology and Drug Safety· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
49
citations

How this was built: Screen · Findings · About