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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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Clinical practice guidelines implementation
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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
aboutaboutness

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

2,993 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.
2,993 works in the cohort · of 4,299,418page 11 of 60

Labels cover 42 of 2,993 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 2,993 of 2,993 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.

affunlabeled
Evidence-informed evidence-making
Kalipso Chalkidou, Tom Walley, Anthony J. Culyer, Peter Littlejohns, Andrew Hoy
2008· article· en· Journal of Health Services Research & Policy· Medicine
machine prediction:candidate · metaresearchconsensus · metaresearch
23
citations
affaboutunlabeled
Strategic clinical networks in Alberta
Tom Noseworthy, Tracy Wasylak, Blair J. O’Neill
2015· review· en· Healthcare Management Forum· Medicine
machine prediction:candidate · noneconsensus · none
23
citations
affvenueaboutunlabeled
Alberta’s Strategic Clinical Networks
Verna Yiu, François Belanger, Kathryn G. Todd
2019· article· en· Canadian Medical Association Journal· Medicine
machine prediction:candidate · noneconsensus · none
22
citations
affunlabeled
DO GUIDELINES INFLUENCE PRACTICE?
Paul W. Armstrong
2003· review· en· Heart· Medicine
machine prediction:candidate · metaresearchconsensus · none
22
citations
affunlabeled
The role of scoping reviews in guideline development
Danielle Pollock, Hanan Khalil, Catrin Evans, Christina Godfrey, Dawid Pieper, Lyndsay Alexander +14 more
2024· editorial· en· Journal of Clinical Epidemiology· Medicine
machine prediction:candidate · metaresearchconsensus · metaresearch
22
citations
afffundunlabeled
Format guidelines to make them vivid, intuitive, and visual
Judith Versloot, Agnes Grudniewicz, Ananda Chatterjee, Leigh Hayden, Monika Kastner, Onil Bhattacharyya
2015· review· en· International Journal of Evidence-Based Healthcare· Medicine
machine prediction:candidate · metaresearchconsensus · none
22
citations
afffundvenueaboutunlabeled
Online clinical pathway for managing adults with chronic kidney disease
Craig Curtis, Carlee Balint, Yazid N. Al Hamarneh, Maoliosa Donald, Ross T. Tsuyuki, Kerry McBrien +2 more
2015· article· en· Canadian Pharmacists Journal / Revue des Pharmaciens du Canada· Medicine
machine prediction:candidate · noneconsensus · none
22
citations
aboutno affunlabeled
Analysis of the quality of clinical practice guidelines on established ischemic stroke
M. Asunción Navarro Puerto, Iñaki Gutiérrez‐Ibarluzea, Oscar Ruiz, Francisco Moniche Álvarez, Rocío Gómez Herreros, Ruth Engelhardt Pintiado +2 more
2008· review· en· International Journal of Technology Assessment in Health Care· Medicine
machine prediction:candidate · metaresearchconsensus · metaresearch
21
citations

How this was built: Screen · Findings · About