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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
Evidence
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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 54 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.

venueaboutno affunlabeled
Canada's ehealth software "Tower of Babel"
Paul Webster
2010· article· en· Canadian Medical Association Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
STROBE reporting guidelines for health equity
Eric I. Benchimol, Sinéad Langan
2025· editorial· en· BMJ· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
6
citations
affunlabeled
Economic evaluation in renal disease
Scott Klarenbach
2007· article· en· Journal of Nephrology· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations
afffundunlabeled
Bayesian Decision Curve Analysis With Bayesdca
Giuliano Netto Flores Cruz, Keegan Korthauer
2024· article· en· Statistics in Medicine· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
6
citations
venueno affunlabeled
10.51847/eSW9J2O
2000· article· en· Time to knit· Economics, Econometrics and Finance
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
6
citations
affunlabeled
Health Policy and Outcomes 2006
Renée Lyons, Anthony Rudd
2007· review· en· Stroke· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations
fundno affunlabeled
An equity checklist : a framework for health technology assessments
Anthony J. Culyer, Yvonne Bombard
2011· preprint· en· White Rose Research Online (University of Leeds, The University of Sheffield, University of York)· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
6
citations
affno abstractunlabeled
A critique of the fragility index – Authors' reply
Joseph C. Del Paggio, Ian F. Tannock
2019· letter· en· The Lancet Oncology· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
6
citations
affunlabeled
Health Care Prioritization: A Clinician's Duty
Lianne Barnieh, Cam Donaldson, Braden Manns
2014· article· en· Canadian Journal of Kidney Health and Disease· 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
affunlabeled
AGING AND HEALTH TECHNOLOGY ASSESSMENT: AN IDEA WHOSE TIME HAS COME
Don Juzwishin, Heather McNeil, Jeonghoon Ahn, Yingyao Chen, Americo Cicchetti, Naoto Kume +2 more
2018· article· en· International Journal of Technology Assessment in Health Care· 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
affunlabeled
Demonstrating the influence of HTA: INAHTA member stories of HTA impact
Sophie Werkö, Tracy Merlin, Laurie Lambert, Paul Fennessy, Ana Pérez Galán, Tara Schuller
2020· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations
affvenueno abstractunlabeled
The axiom of Rose
Paul Malik
2006· article· en· Canadian Journal of Cardiology· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Core competencies for ethics experts in health technology assessment
Pietro Refolo, Kenneth Bond, Bart Bloemen, Ilona Autti‐Rämö, Bjørn Hofmann, Claudia Mischke +8 more
2020· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
6
citations

How this was built: Screen · Findings · About