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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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Journal of Clinical Epidemiology
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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.

1,510 results · 1 filter active ·
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20002025
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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.
1,510 works in the cohort · of 4,299,418page 1 of 31

Labels cover 96 of 1,510 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 1,510 of 1,510 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 abstractunlabeled
GRADE guidelines: 3. Rating the quality of evidence
Howard Balshem, Mark Helfand, Holger J. Schünemann, Andrew D Oxman, Regina Kunz, Jan Brożek +4 more
2011· article· en· Journal of Clinical Epidemiology· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
8,174
citations
affno abstractunlabeled
Scoping reviews: time for clarity in definition, methods, and reporting
Heather Colquhoun, Danielle Levac, Kelly K. O’Brien, Sharon E. Straus, Andrea C. Tricco, Laure Perrier +2 more
2014· article· en· Journal of Clinical Epidemiology· Decision Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
2,793
citations
affno abstractgemma · metaresearchgpt · metaresearchmodels split
GRADE guidelines 6. Rating the quality of evidence—imprecision
Gordon Guyatt, Andrew D Oxman, Regina Kunz, Jan Brożek, Pablo Alonso‐Coello, David M. Rind +14 more
2011· article· en· Journal of Clinical Epidemiology· Medicine
machine prediction:candidate · metaresearchconsensus · none
2,682
citations
affno abstractunlabeled
GRADE guidelines: 8. Rating the quality of evidence—indirectness
Gordon Guyatt, Andrew D Oxman, Regina Kunz, James Woodcock, Jan Brożek, Mark Helfand +11 more
2011· article· en· Journal of Clinical Epidemiology· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
1,855
citations
affno abstractunlabeled
Methods for assessing responsiveness
Janice Husted, Richard J. Cook, Vernon T. Farewell, D. Gladman
2000· review· en· Journal of Clinical Epidemiology· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
1,470
citations
affno abstractunlabeled
GRADE guidelines: 9. Rating up the quality of evidence
Gordon Guyatt, Andrew D Oxman, Shahnaz Sultan, Paul Glasziou, Elie A. Akl, Pablo Alonso‐Coello +14 more
2011· article· en· Journal of Clinical Epidemiology· Medicine
machine prediction:candidate · metaresearchconsensus · none
1,332
citations

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