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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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Mobile Health and mHealth Applications
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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.

4,475 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.
4,475 works in the cohort · of 4,299,418page 67 of 90

Labels cover 50 of 4,475 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 4,475 of 4,475 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
Editorial: Equitable digital medicine and home health care
Francesco De Micco, Anna De Benedictis, Emanuele Lettieri, Vittoradolfo Tambone
2023· editorial· en· Frontiers in Public Health· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Helina
Ghislain B. Kouematchoua Tchuitcheu
2019· article· en· Yearbook of Medical Informatics· Health Professions
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
venueno affno abstractunlabeled
How Can Diabetes Applications Be Better?
Kerri Sparling
2015· article· en· Canadian Journal of Diabetes· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
mHealth Portable Systems and Platforms
S. S. M. Zahir, Radwa Hammad
2015· book-chapter· en· Springer series in bio-/neuroinformatics· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affno abstractunlabeled
There's an App for That, But Does It Work?
Ann Chen Wu
2019· letter· en· The Journal of Allergy and Clinical Immunology In Practice· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About