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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 25 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.

affunlabeled
Comparative Effectiveness Research: Challenges for Medical Journals
Harold C. Sox, Mark Helfand, Jeremy Grimshaw, Kay Dickersin, David Tovey, J. André Knottnerus +1 more
2010· article· en· Journal of Clinical Epidemiology· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
29
citations
affno abstractunlabeled
Modifying NICE’s Approach to Equity Weighting
Mike Paulden, Christopher McCabe
2021· article· en· PharmacoEconomics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
29
citations
afffundno abstractunlabeled
The Role of Models Within Economic Analysis
Doug Coyle, Karen M. Lee, Bernie J. O Brien
2002· review· en· PharmacoEconomics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
29
citations
affno abstractunlabeled
The art of priority setting
Mireille Goetghebeur, Hector Castro-Jaramillo, Rob Baltussen, Norman Daniels
2017· article· en· The Lancet· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
29
citations
fundno affunlabeled
Exclusion Criteria as Measurements I: Identifying Invalid Responses
Barry Dewitt, Baruch Fischhoff, Alexander Davis, Stephen B. Broomell, Mark S. Roberts, Janel Hanmer
2019· article· en· Medical Decision Making· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
28
citations
affno abstractunlabeled
How to make cardiology clinical trials more inclusive
Faı̈ez Zannad, Otávio Berwanger, Stefano Corda, Martín Cowie, Habib Gamra, C. Michael Gibson +15 more
2024· review· en· Nature Medicine· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
28
citations
affunlabeled
Registries for orphan drugs: generating evidence or marketing tools?
Carla E. M. Hollak, Sandra Sirrs, Sibren van den Berg, Vincent van der Wel, Mirjam Langeveld, Hanka Dekker +2 more
2020· article· en· Orphanet Journal of Rare Diseases· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
28
citations

How this was built: Screen · Findings · About