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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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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.

2,654 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.
2,654 works in the cohort · of 4,299,418page 47 of 54

Labels cover 27 of 2,654 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 2,654 of 2,654 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.

aboutno affno abstractunlabeled
Communicating science
The Lancet
2006· editorial· en· The Lancet· Medicine
machine prediction:candidate · scholarly_communicationconsensus · none
2
citations
aboutno affno abstractunlabeled
Canada’s feminist foreign aid agenda
The Lancet
2017· editorial· en· The Lancet· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Death in children with epilepsy
Carol Camfield, Peter Camfield
2002· article· en· The Lancet· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
HIV/AIDS data in South Africa
Christian Fiala, Étienne de Harven, Andrew Herxheimer, Claus Kohnlein, Sam Mhlongo, Gordon T. Stewart
2002· letter· en· The Lancet· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Primary-care reform in the USA
Janusz Kaczorowski
2010· letter· en· The Lancet· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affno abstractunlabeled
Offline: Canada's big promise
Richard Horton
2014· article· en· The Lancet· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Making primary care people-centred
Janusz Kaczorowski
2014· letter· en· The Lancet· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
A blow to the fight against snakebite
Jonn Kmech
2010· article· en· The Lancet· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affno abstractunlabeled
Canada's G8 health leadership
The Lancet
2010· editorial· en· The Lancet· Health Professions
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Disease burden descriptions in trial protocols
Brendan Tao, Jim Shenchu Xie, Radha P. Kohly, Edward Margolin
2024· letter· en· The Lancet· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
2
citations
afffundno abstractunlabeled
Weighing up dietary patterns
Arne Astrup, Jennie Brand‐Miller, David J.A. Jenkins, Geoffrey Livesey, Walter C. Willett
2016· letter· en· The Lancet· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Can deinstitutionalisation contribute to exclusion?
Tarun Bastiampillai, Stephen Allison, Richard O’Reilly, Júlio Licinio, Steven S. Sharfstein
2018· letter· en· The Lancet· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Questioning statin therapy for older patients
John Abramson, Curt D. Furberg, Nicholas P. Jewell, James M Wright
2020· letter· en· The Lancet· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Not arthritis
Évelyne Vinet, Navdeep Tangri, Christian A. Pineau
2007· article· en· The Lancet· Medicine
machine prediction:candidate · noneconsensus · none
1
citations
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