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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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Diabetes, Cardiovascular Risks, and Lipoproteins
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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
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

2,212 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.
2,212 works in the cohort · of 4,299,418page 28 of 45

Labels cover 11 of 2,212 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 2,212 of 2,212 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
10.1016/s0084-3873(13)00339-8
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
6
citations
affno abstractunlabeled
Calculation of LDL apoB
Allan D. Sniderman, André Tremblay, Jacqueline de Graaf, Patrick Couture
2014· article· en· Atherosclerosis· Medicine
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Making Diabetes Management Routine
Beth Leggett Cameron
2002· review· en· AJN American Journal of Nursing· Medicine
machine prediction:candidate · noneconsensus · none
6
citations
affvenueunlabeled
Metabolic syndrome: Waist not want not
E. Weir
2004· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
6
citations
venueno affno abstractunlabeled
Which Nutritional Factors Are Good for HDL?
Hidekatsu Yanai, Norio Tada
2018· article· en· Journal of Clinical Medicine Research· Medicine
machine prediction:candidate · noneconsensus · none
6
citations
affno abstractunlabeled
Erroneous HbA1c results in a patient with elevated HbC and HbF
Joy Adekanmbi, Trefor Higgins, Karina Rodríguez-Capote, Dylan Thomas, Jeffrey Winterstein, Tara Dixon +5 more
2016· article· en· Clinica Chimica Acta· Medicine
machine prediction:candidate · noneconsensus · none
6
citations
aboutno affunlabeled
Cubbing in proapolipoprotein maturation
Godfrey S. Getz, Catherine A. Reardon
2011· letter· en· Journal of Lipid Research· Medicine
machine prediction:candidate · noneconsensus · none
6
citations
venueno affno abstractunlabeled
Risk Factors for Type 2 Diabetes in the Multiethnic Cohort
Gertraud Maskarinec, Bruce S. Kristal, Lynne R. Wilkens, Gino Quintal, David Bogumil, Veronica Wendy Setiawan +1 more
2023· article· en· Canadian Journal of Diabetes· Medicine
machine prediction:candidate · noneconsensus · none
6
citations
aboutno affunlabeled
Why do we need a new journal now?
Nigishi Hotta
2010· article· en· Journal of Diabetes Investigation· Medicine
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Diagnosis of remnant hyperlipidaemia
Martine Paquette, Sophie Bernard, Alexis Baass
2022· review· en· Current Opinion in Lipidology· Medicine
machine prediction:candidate · noneconsensus · none
6
citations

How this was built: Screen · Findings · About