MétaCan
Menu
Cohort builder

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.

Search term
Author
Year range
→
Sort
Language
Type
Field
Venue
Topic
Health Systems, Economic Evaluations, Quality of Life
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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 ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
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 51 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.

afffundvenueno abstractunlabeled
Letter to the editor
Tisha Joy, Robert A. Hegele
2009· letter· en· Canadian Journal of Cardiology· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
How does HTA addresses current social expectations? An international survey
Hubert Gagnon, Georges-Auguste Legault, Christian Bellemare, Monelle Parent, Pierre Dagenais, Suzanne K.-Bédard +5 more
2020· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
7
citations
affunlabeled
Challenges of calculating cost-effectiveness thresholds
Laura Vallejo‐Torres, Karl Claxton, Laura C. Edney, Jonathan Karnon, James Lomas, Jessica Ochalek +3 more
2023· letter· en· The Lancet Global Health· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
7
citations
affno abstractunlabeled
Evidence-Based Decision-Making 3: Health Technology Assessment
Daria O’Reilly, Kaitryn Campbell, Meredith Vanstone, James M. Bowen, Lisa Schwartz, Nazila Assasi +1 more
2015· article· en· Methods in molecular biology· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Systems thinking in health technology assessment: a scoping review
Marina Richardson, Lauren Ramsay, Joanna Bielecki, Whitney Berta, Beate Sander
2021· review· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Commentary
H. David Banta, Egon Jonsson
2006· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · insufficient_payloadconsensus · none
7
citations
affunlabeled
A test of prospect theory
David Feeny, Ken Eng
2005· article· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
7
citations
fundno affunlabeled
Early technology review: towards an expedited pathway
Leslie Levin, Murray Sheldon, Robert S. McDonough, Naomi Aronson, Maroeska M. Rovers, C. Michael Gibson +2 more
2024· review· en· International Journal of Technology Assessment in Health Care· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
7
citations

How this was built: Screen · Findings · About