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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
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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 134 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.

fundno affno abstractunlabeled
Value-based assessment of new medical technologies: towards a robust methodological framework for the application of multiple criteria decision analysis in the context of health technology assessment
Aris Angelis, Panos Kanavos
2016· article· en· London School of Economics and Political Science Research Online (London School of Economics and Political Science)· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
0
citations
affvenueno abstractunlabeled
Clinician’s Commentary on Gervais-Hupé et al.
Liz Harvey, Patricia Thille
2023· article· en· Physiotherapy Canada· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
MedPulse
Matthew Ahn, Hannah Silverman
2022· article· en· The Meducator· Economics, Econometrics and Finance
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
afffundaboutunlabeled
2025 National NeuGeneration Case Competition: Neurodegenerative Diseases
Eileen Danaee, Nnamdi Ndubuka, Tyler Rotholz, James Sunwoo, Sophie Guerrico
2025· article· en· Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal· Economics, Econometrics and Finance
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Disease Burden Measures: a Review
Kiera L Goff, Lindsay N. Boyers, Chanté Karimkhani, Jason P. Lott, Robert P. Dellavalle
2015· review· en· Current Dermatology Reports· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Outputs from Probabilistic Sensitivity Analysis
Richard Edlin, Christopher McCabe, Claire Hulme, Peter S Hall, Judy Wright
2015· book-chapter· en· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
DEI needs to fix systems, not people
Jeffrey To
2025· article· en· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About