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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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British Journal of Sports 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.

affaffiliation
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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.

1,221 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.
1,221 works in the cohort · of 4,299,418page 14 of 25

Labels cover 3 of 1,221 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 1,221 of 1,221 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.

affunlabeled
Cochrane Reviews: new blocks on the kids
Ian Shrier
2003· article· en· British Journal of Sports Medicine· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
16
citations
fundno affunlabeled
Who owns the information?
John Orchard
2002· review· en· British Journal of Sports Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
16
citations
affunlabeled
Infographic. Sex differences and ACL injuries
Hana Marmura, Dianne Bryant, Alan Getgood
2021· article· en· British Journal of Sports Medicine· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
16
citations
aboutno affunlabeled
Injuries of the sporting knee
I Corry, Jeremy S. Webb
2000· article· en· British Journal of Sports Medicine· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
15
citations
affunlabeled
ICON 2023: International Scientific Tendinopathy Symposium Consensus – the core outcome set for Achilles tendinopathy (COS-AT) using a systematic review and a Delphi study of professional participants and patients
Robert‐Jan de Vos, Karin Grävare Silbernagel, Peter Malliaras, Tjerk Sleeswijk Visser, Håkan Alfredson, Inge van den Akker‐Scheek +38 more
2024· review· en· British Journal of Sports Medicine· Medicine
machine prediction:candidate · metaresearchconsensus · none
15
citations
affunlabeled
CyberAbuse in sport: beware and be aware!
Emma Kavanagh, Margo Mountjoy
2024· editorial· en· British Journal of Sports Medicine· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
The patient as person: an update
Dawn P. Richards
2020· editorial· en· British Journal of Sports Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
14
citations

How this was built: Screen · Findings · About