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 133 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.

affno abstractunlabeled
Response
John C. Sinclair, Richard J. Cook, Gordon Guyatt, Stephen G. Pauker
2002· article· en· Journal of Clinical Epidemiology· Economics, Econometrics and Finance
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Priority climate and health modelling needs
Kristie L. Ebi, Peng Bi, Kathryn Bowen, Michael Bräuer, Paul Lester Chua, Felipe J. Colón‐González +29 more
2025· article· en· The Lancet Planetary Health· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
TCT-54 Additive Prognostic Value Of The Global Registry Of Acute Coronary Events Score Over Other Risk Scores For In-Hospital Outcome Prediction In Patients Presenting With ST-Elevation Myocardial Infarction Treated With Primary Percutaneous Coronary Intervention
Lorenzo Azzalini, Razi Khan, Malek Al‐Hawwas, Raja Hatem, Annik Fortier, Philippe L. L’Allier +1 more
2014· article· en· Journal of the American College of Cardiology· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affvenueno abstractunlabeled
Costing Health Care Procedures: Art or Science?
Gillian Currie, Braden Manns
2002· letter· en· Canadian Journal of Gastroenterology· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Investigating ADEPT's Utility: An Exploration of the Literature
Omar Elazhary, Enrique Larios Vargas, Alessandra Maciel Paz Milani, Margaret‐Anne Storey
2021· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Fragility of Results in Ophthalmology Randomized Controlled Trials
Carl Shen, Isabel Shamsudeen, Forough Farrokhyar, Kourosh Sabri
2017· article· en· Investigative Ophthalmology & Visual Science· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
0
citations
affaboutunlabeled
How is Funding Medical Research Better for Patients?
Jennifer Zwicker, J.C. Herbert Emery
2015· article· en· The School of Public Policy Publications· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · none
0
citations
affaboutunlabeled
Acknowledgements
Gregory P. Marchildon, Sara Allin
2021· book-chapter· en· University of Toronto Press eBooks· Economics, Econometrics and Finance
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affunlabeled
The Table 2 Fallacy and Overfitting: A Persistent Problem in Contemporary Research?
Víctor Juan Vera-Ponce, Jhosmer Ballena-Caicedo, Lupita Ana Maria Valladolid-Sandoval, Fiorella E. Zuzunaga-Montoya, Carmen Inés Gutierrez De Carrillo
2025· article· en· International Journal of Statistics in Medical Research· Economics, Econometrics and Finance
machine prediction:candidate · metaresearchconsensus · metaresearch
0
citations
fundno affunlabeled
The costs of intensive care
Leona Hakkaart‐van Roijen, Samuel Tan, Clazien Bouwmans, Mustafa al, Peter E. Spronk, Jan Bakker
2007· article· en· Critical Care· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Risk Assessment in Clinical Decision Making
Harry S. Shannon, Alejandro R. Jadad
2005· other· en· Encyclopedia of Biostatistics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Highly Cited Works on Human Clinical Trials
M. Surulinathi, Arputha Sahaya Rani Y, P Divya, T Jayasuriya, R K E R N
2021· article· en· Zenodo (CERN European Organization for Nuclear Research)· Economics, Econometrics and Finance
machine prediction:candidate · metaresearch+bibliometricsconsensus · none
0
citations

How this was built: Screen · Findings · About