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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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Obesity, Physical Activity, Diet
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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.

5,973 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.
5,973 works in the cohort · of 4,299,418page 106 of 120

Labels cover 15 of 5,973 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 5,973 of 5,973 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 affunlabeled
Statural growth of children aged 11 and 12 years
Orivaldo Florêncio de Souza, Cândido Simões Pires Neto
2003· article· en· LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
Neighbourhood Income Affects Obesity
Michael Hayes, Lisa Oliver
2015· other· en· York University Digital Library (York University)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Fit kids?
Juan Miguel Pedraza
2016· article· UND Scholarly Commons (University of North Dakota)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Eating habits of a sample of children in Vila Nova de Gaia - Portugal
Ângela Moraes Teixeira, Alda Alvim, Cláudia Afonso, Patrícia Padrão, Bruno Oliveira, Maria Daniel Vaz de Almeida
2010· article· en· Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)· Medicine
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About