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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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Health Literacy and Information Accessibility
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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.

2,100 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.
2,100 works in the cohort · of 4,299,418page 1 of 42

Labels cover 15 of 2,100 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 2,100 of 2,100 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.

afffundaboutunlabeled
eHEALS: The eHealth Literacy Scale
Cameron D. Norman, Harvey A. Skinner
2006· article· de· Journal of Medical Internet Research· Health Professions
machine prediction:candidate · noneconsensus · none
2,724
citations
afffundgpt · no categorygrok · no categoryopus · no categorymodels agree
What Is eHealth (3): A Systematic Review of Published Definitions
Hans Oh, Alejandro R. Jadad, Carlos Rizo-Maestre, Murray Enkin, John Powell, Claudia Pagliari
2005· review· en· Journal of Medical Internet Research· Health Professions
machine prediction:candidate · noneconsensus · none
1,037
citations
affunlabeled
Health Information—Seeking Behavior
Sylvie Lambert, Carmen G. Loiselle
2007· article· en· Qualitative Health Research· Health Professions
machine prediction:candidate · noneconsensus · none
916
citations
afffundvenueno abstractunlabeled
Mental Health Literacy
Stan Kutcher, Yifeng Wei, Connie Coniglio
2016· article· en· The Canadian Journal of Psychiatry· Health Professions
machine prediction:candidate · noneconsensus · none
900
citations
fundno affunlabeled
Addressing health literacy in patient decision aids
Kirsten McCaffery, Margaret Holmes‐Rovner, Sian K. Smith, David R. Rovner, Don Nutbeam, Marla L. Clayman +3 more
2013· review· en· BMC Medical Informatics and Decision Making· Health Professions
machine prediction:candidate · noneconsensus · none
276
citations
affunlabeled
Understanding the Health Literacy of America
Carolyn Crane Cutilli, Ian M. Bennett
2009· article· en· Orthopaedic Nursing· Health Professions
machine prediction:candidate · noneconsensus · none
238
citations
affno abstractunlabeled
Literacy, Cognitive Function, and Health: Results of the LitCog Study
Michael S. Wolf, Laura M. Curtis, Elizabeth A. Wilson, William Revelle, Katherine Waite, Samuel G. Smith +5 more
2012· article· en· Journal of General Internal Medicine· Health Professions
machine prediction:candidate · noneconsensus · none
206
citations
affunlabeled
Use of the Internet by Women with Breast Cancer
Joshua Fogel, Steven M. Albert, Freya Schnabel, Beth Ann Ditkoff, Alfred I. Neugut
2002· article· en· Journal of Medical Internet Research· Health Professions
machine prediction:candidate · noneconsensus · none
200
citations
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