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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.

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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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Frailty in Older Adults
Retraction
Abstract
Evidence source
Study design
Label agreement
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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.

3,562 results · 1 filter active ·
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20002025
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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.
3,562 works in the cohort · of 4,299,418page 40 of 72

Labels cover 11 of 3,562 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 3,562 of 3,562 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
La fragilité des personnes âgées
Véronique Provencher, Louise Demers
2013· book-chapter· fr· Presses de l’EHESP eBooks· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
afffundvenueno abstractunlabeled
Admission Criteria in Short-term Geriatric Assessment Units
Charo Rodríguez, Marie‐Jeanne Kergoat, Judith Latour, Paule Lebel, André‐Pierre Contandriopoulos
2003· article· en· Canadian Journal of Public Health· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Regional Differences in Incident Prefrailty and Frailty
Sarah E. Tom, Allison Wyman, Nancy Fúgate Woods, Frederick A. Anderson, Jonathan D. Adachi, Roland Chapurlat +18 more
2017· article· en· Journal of Women s Health· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
affunlabeled
Frailty in nursing home residents: a scoping review protocol
Thanuja De Silva, Sally Suriani Ahip, Olga Theou, Cătălin Tufănaru, Renuka Visvanathan, Kandiah Umapathysivam
2017· review· en· The JBI Database of Systematic Reviews and Implementation Reports· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
aboutno affunlabeled
PRÉ-FRAGILIDADE EM PESSOAS IDOSAS: PREVALÊNCIA E FATORES ASSOCIADOS
Adriana Delmondes de Oliveira, Annelita Almeida Oliveira Reiners, Rosemeiry Capriata de Souza Azevedo, Kátia Moreira da Silva, Ageo Mário Cândido da Silva
2022· article· pt· Texto & Contexto - Enfermagem· Medicine
machine prediction:candidate · noneconsensus · none
3
citations
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