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
Indian Journal of Medical Ethics
Topic
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.

44 results · 1 filter active ·
Results by year
20052025
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.
44 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 44 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 44 of 44 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
Combating corruption in the pharmaceutical arena
Joel Lexchin, Jillian Clare Köhler, Marc‐André Gagnon, James Crombie, Paul D. Thacker, Adrienne Shnier
2018· article· en· Indian Journal of Medical Ethics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Starting the conversation: CRISPR’s role in India
Farhad R. Udwadia, Shivam Singh
2019· article· en· Indian Journal of Medical Ethics· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
8
citations
affaboutunlabeled
Opioid promotion in Canada: A narrative review
Joel Lexchin
2024· review· en· Indian Journal of Medical Ethics· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Whistleblowing without names is hearsay
David Healy
2022· letter· en· Indian Journal of Medical Ethics· Health Professions
machine prediction:candidate · research_integrityconsensus · none
4
citations
affunlabeled
Paper Annotation with Learner Models
Tiffany Y. Tang, Gordon McCalla
2005· article· en· Indian Journal of Medical Ethics· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Sports ethics: New challenges for new times
Janelle Joseph, Padma Prakash
2025· article· en· Indian Journal of Medical Ethics· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
fundno affunlabeled
Response: caught between two world views
Roopa Devadasan
2011· letter· en· Indian Journal of Medical Ethics· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
On violence against patients
2024· article· en· Indian Journal of Medical Ethics· Health Professions
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Nancy Olivieri: Sometimes, truth has only one face
Sandhya Srinivasan
2024· article· en· Indian Journal of Medical Ethics· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · research_integrityconsensus · none
0
citations
affunlabeled
To be forgotten with age
Vrinda Nair
2022· article· en· Indian Journal of Medical Ethics· Psychology
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About