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
Artificial Intelligence in Healthcare
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.

843 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.
843 works in the cohort · of 4,299,418page 14 of 17

Labels cover 7 of 843 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 843 of 843 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

aboutno affunlabeled
COVID-19 and Diabetes Mellitus
Swaroopa Chakole Kirti Agrawal
2021· article· en· Psychology and Education Journal· Health Professions
distilled prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affunlabeled
Correction: A Personalized Ontology-Based Decision Support System for Complex Chronic Patients: Retrospective Observational Study
Esther Román-Villarán, Celia Álvarez-Romero, Alicia Martínez-García, Germán Antonio Escobar-Rodríguez, María José García-Lozano, Bosco Barón‐Franco +4 more
2023· erratum· en· JMIR Formative Research· Health Professions
distilled prediction:candidate · metaepi_narrow+sts+research_integrity+insufficient_payloadconsensus · research_integrity+insufficient_payload
0
citations
affunlabeled
ProQuest Coronavirus Research Database
Marcia Salmon
2020· article· en· The Charleston Advisor· Health Professions
distilled prediction:candidate · sts+research_integrity+insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Preface
2021· article· en· Journal of Physics Conference Series· Health Professions
distilled prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
CardioNet.AI - Heart Disease Predictor Model
Abubakar Maulani Pungiwale
2025· article· en· INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT· Health Professions
distilled prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Obesity Level Prediction Using Multinomial Logistic Regression
Shruti Srivatsan
2023· book-chapter· en· ˜The œSpringer series in applied machine learning· Health Professions
distilled prediction:candidate · metaepi_narrow+sts+research_integrity+insufficient_payloadconsensus · research_integrity
0
citations
affunlabeled
Creating a Basic ChatGPT Client in JavaScript
Bruce R. Hopkins
2025· book-chapter· en· Apress eBooks· Health Professions
distilled prediction:candidate · metaepi_narrow+research_integrity+insufficient_payloadconsensus · research_integrity+insufficient_payload
0
citations
aboutno affunlabeled
Preface
2021· article· en· IOP Conference Series Materials Science and Engineering· Health Professions
distilled prediction:candidate · insufficient_payloadconsensus · none
0
citations

How this was built: Screen · Findings · About