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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.

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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.

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 16 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.

affgemma · metaresearchgpt · no categorymodels split
Merging of the National Cancer Institute–funded cooperative oncology group data with an administrative data source to develop a more effective platform for clinical trial analysis and comparative effectiveness research: a report from the Children's Oncology Group
Richard Aplenc, Brian T. Fisher, Yuanjie Huang, Yuelin Li, Todd A. Alonzo, Robert B. Gerbing +7 more
2012· article· en· Pharmacoepidemiology and Drug Safety· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
49
citations
affunlabeled
What Should Be Reported in a Methods Section on Utility Assessment?
Peep F. M. Stalmeier, Mary K. Goldstein, Ann Holmes, Leslie Lenert, John M. Miyamoto, Anne M. Stiggelbout +2 more
2001· article· en· Medical Decision Making· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
49
citations
affno abstractunlabeled
Health technology assessment in universal health coverage
Kalipso Chalkidou, Robert Marten, Derek Cutler, Tony Culyer, Richard Smith, Yot Teerawattananon +16 more
2013· article· en· The Lancet· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
48
citations
afffundunlabeled
Reporting guidelines for modelling studies
Carol Bennett, Douglas G. Manuel
2012· article· en· BMC Medical Research Methodology· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
48
citations
affunlabeled
REVEALING AND ACKNOWLEDGING VALUE JUDGMENTS IN HEALTH TECHNOLOGY ASSESSMENT
Bjørn Hofmann, Irina Cleemput, Kenneth Bond, Tanja Krones, Sigrid Droste, Darío Sacchini +1 more
2014· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
48
citations
affunlabeled
How to Measure and Interpret Quality Improvement Data
Rory McQuillan, Samuel A. Silver, Ziv Harel, Adam V. Weizman, Alison Thomas, Chaim M. Bell +3 more
2016· article· en· Clinical Journal of the American Society of Nephrology· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
48
citations
affno abstractunlabeled
Piloting the NPF data-driven quality improvement initiative
Michael S. Okun, Andrew Siderowf, John G. Nutt, Gerald T. O’Conner, Bastiaan R. Bloem, Elaine M. Olmstead +10 more
2010· article· en· Parkinsonism & Related Disorders· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
48
citations
affno abstractunlabeled
Putting palliative care on the global health agenda
Richard A. Powell, Faith Mwangi-Powell, Lukas Radbruch, Gavin Yamey, Eric L. Krakauer, Dingle Spence +6 more
2015· article· en· The Lancet Oncology· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
47
citations
affunlabeled
Defining decision thresholds for judgments on health benefits and harms using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence to Decision (EtD) frameworks: a protocol for a randomised methodological study (GRADE-THRESHOLD)
Gian Paolo Morgano, Lawrence Mbuagbaw, Nancy Santesso, Feng Xie, Jan Brożek, Uwe Siebert +10 more
2022· article· en· BMJ Open· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
46
citations

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