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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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BMC Medicine
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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.

538 results · 1 filter active ·
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20032025
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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.
538 works in the cohort · of 4,299,418page 1 of 11

Labels cover 14 of 538 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 538 of 538 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.

afffundunlabeled
RAMESES publication standards: realist syntheses
Geoff Wong, Trisha Greenhalgh, Gill Westhorp, Jeanette Buckingham, Ray Pawson
2013· article· en· BMC Medicine· Health Professions
machine prediction:candidate · metaresearchconsensus · metaresearch
1,347
citations
afffundgemma · metaresearchgpt · metaresearchmodels agree
A scoping review of rapid review methods
Andrea C. Tricco, Jesmin Antony, Wasifa Zarin, Lisa Strifler, Marco Ghassemi, John D. Ivory +4 more
2015· review· en· BMC Medicine· Decision Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
1,156
citations
fundno affunlabeled
RAMESES II reporting standards for realist evaluations
Geoff Wong, Gill Westhorp, Ana Manzano, Joanne Greenhalgh, Justin Jagosh, Trisha Greenhalgh
2016· article· en· BMC Medicine· Health Professions
machine prediction:candidate · metaresearchconsensus · metaresearch
918
citations
afffundaboutunlabeled
Post-stroke dementia – a comprehensive review
Milija Mijajlović, Aleksandra Pavlović, Michael Brainin, Wolf-Dieter Heiss, Terence J. Quinn, Hege Ihle-Hansen +27 more
2017· review· en· BMC Medicine· Medicine
machine prediction:candidate · noneconsensus · none
710
citations
afffundunlabeled
RAMESES publication standards: meta-narrative reviews
Geoff Wong, Trisha Greenhalgh, Gill Westhorp, Jeanette Buckingham, Ray Pawson
2013· article· en· BMC Medicine· Decision Sciences
machine prediction:candidate · metaresearchconsensus · metaresearch
599
citations
328
citations
aboutno affunlabeled
Research impact: a narrative review
Trisha Greenhalgh, James Raftery, Matthew Glover
2016· review· en· BMC Medicine· Health Professions
machine prediction:candidate · metaresearchconsensus · none
327
citations

How this was built: Screen · Findings · About