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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 and Health Practices
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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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venuejournal
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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.

1,836 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.
1,836 works in the cohort · of 4,299,418page 29 of 37

Labels cover 11 of 1,836 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 1,836 of 1,836 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.

venueno affno abstractunlabeled
Call for Original Papers: Focus Issue on Obesity
2024· article· en· Canadian Journal of Cardiology· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affunlabeled
Nuts, bolts and short-chain fatty acids
Monica Kidd
2011· article· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Occurrence Download
2017· dataset· en· Global Biodiversity Information Facility· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Combating weight bias
Don Mathew
2023· article· en· Journal of Hospital Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Obesity in Canada
2011· dataset· en· PsycEXTRA Dataset· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0029-7437(06)72350-3
2000· article· en· Time to knit· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
Association of Socioeconomic Factors with Success in the Treatment of Obesity
Marcela Rodríguez-Flores, Verónica Vázquez‐Velázquez, Gabriela Torres Mejía, Valeria Soto Fuentes, Lucia Peniche Peniche, Rodrigo Maciel +2 more
2015· article· en· Canadian Journal of Diabetes· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
P6
Katrina Sprengelmeyer, Karen Chapman‐Novakofski
2006· article· en· Journal of Nutrition Education and Behavior· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueaboutno affunlabeled
Older and wiser
Shelley Martin
2000· article· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0029-7437(06)71398-2
2000· article· en· Time to knit· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Lifestyle Health Risks
Alex C. Michalos
2014· book-chapter· en· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affvenueno abstractunlabeled
How can we explain the resistance to lose weight?
A. Dumais, Brassard P, Angelo Tremblay
2011· article· en· Canadian Journal of Diabetes· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
Canadian global village reality
Meizi He, E.T.S. Li, Stewart B. Harris, Murray W. Huff, Chun Yip Yau, G. Harvey Anderson
2010· article· en· Canadian Family Physician· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
affvenueaboutunlabeled
Who is the bad apple?
Jennifer Pikard
2009· letter· en· Canadian Medical Association Journal· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About