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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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Health Systems, Economic Evaluations, Quality of Life
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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.

6,862 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.
6,862 works in the cohort · of 4,299,418page 56 of 138

Labels cover 97 of 6,862 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 6,862 of 6,862 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.

affvenueunlabeled
Number Needed To… $ave?
Graeme Rocker, Jennifer Verma, Jillian Demmons, Nicole Mittmann
2015· article· en· Clinical and investigative medicine· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
6
citations
affunlabeled
How can we make better health decisions: a Best Buy for all?
Niki O’Brien, Ryan Li, Wanrudee Isaranuwatchai, Saudamini Vishwanath Dabak, Amanda Glassman, Anthony J. Culyer +1 more
2020· preprint· en· Gates Open Research· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations
aboutno affunlabeled
The European Organisation for Research and Treatment of Cancer Quality of Life Utility-Core 10 Dimensions: Development and Investigation of General Population Utility Norms for Canada, France, Germany, Italy, Poland, and the United Kingdom
Micha J. Pilz, Sandra Nolte, Gregor Liegl, Madeleine King, Richard Norman, Helen McTaggart‐Cowan +5 more
2022· article· en· Value in Health· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Responses to Comments of Weis
Na Guo, Carlo A. Marra, Fawziah Marra
2010· letter· en· Health and Quality of Life Outcomes· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations
affvenueunlabeled
Improving Drug Trials for Mild to Moderate Alzheimer's Disease
David B. Hogan
2007· review· en· Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
6
citations
affno abstractunlabeled
Clinical judgement and evidence-based medicine
W. Watson Buchanan, Walter F. Kean
2001· editorial· en· Joint Bone Spine· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations
affno abstractgemma · metaresearchgpt · metaresearchmodels split
Challenges in the selection and measurement of outcomes in psychiatric trials
Sophie Juul, Pascal Faltermeier, Faiza Siddiqui, Johanne Juul Petersen, Caroline Barkholt Kamp, Rikke Hermann Jakobsen +9 more
2025· article· en· BMJ evidence-based medicine· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
6
citations

How this was built: Screen · Findings · About