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
Pharmaceutical industry and 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.

1,489 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.
1,489 works in the cohort · of 4,299,418page 10 of 30

Labels cover 35 of 1,489 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 1,489 of 1,489 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.

aboutno affunlabeled
New drugs from old
2006· review· en· Drug and Therapeutics Bulletin· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
8
citations
aboutno affunlabeled
Canadian Patents Database
Marcia Salmon
2009· article· en· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · insufficient_payloadconsensus · none
8
citations
affno abstractunlabeled
Transparency in clinical trial reporting
Paula A. Rochon, Nathan M. Stall, Rachel Savage, An‐Wen Chan
2018· letter· en· BMJ· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · metaresearchconsensus · none
8
citations
affno abstractunlabeled
Media coverage of cancer therapeutics: A review of literature
Fidel Rubagumya, Jacqueline Galica, Eulade Rugengamanzi, Brandon A Niyibizi, Ajay Aggarwal, Richard Sullivan +1 more
2023· review· en· Journal of Cancer Policy· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
8
citations
affaboutunlabeled
Regulation of Pharmaceuticals in Canada
Trudo Lemmens, Ron A. Bouchard
2012· article· en· SSRN Electronic Journal· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
8
citations
venueno affunlabeled
Sponsorship of Medical Textbooks by Drug or Device Companies
Andreas Lundh, Peter C Gøtzsche
2010· article· en· Canadian Medical Education Journal· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · metaresearch+research_integrityconsensus · none
8
citations
venueno affunlabeled
Value-Based Healthcare: Fad or Fabulous?
Stephen Duckett
2019· article· en· A Nudge Too Far? A Nudge at All? On Paying People to Be Healthy· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
8
citations
afffundunlabeled
Science at the Crossroads: Fact or Fiction?
David A. Goldberg
2010· article· en· Journal of Medical Biochemistry· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
7
citations
venueaboutno affunlabeled
A decade of the Common Drug Review
Sarah Spitz
2013· article· en· Canadian Medical Association Journal· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · metaresearchconsensus · none
7
citations
afffundaboutunlabeled
“No one went into pharmacy … to sell a lot of Coca-Cola. It's just sort of a necessary evil” – Community pharmacists' perceptions of front-of-store sales and ethical tensions in the retail environment
Stephanie Gellatly, Alexander J. Moszczynski, Lean Fiedeldey, Sherilyn K. D. Houle, Maxwell J. Smith, Ubaka Ogbogu +3 more
2023· article· en· Exploratory Research in Clinical and Social Pharmacy· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
Evaluation of Industrial Compensation to Cardiologists in 2015
Muhammad Shahzeb Khan, Tariq Jamal Siddiqi, Kaneez Fatima, Haris Riaz, Faisal Khosa, Warren J. Manning +1 more
2017· article· en· The American Journal of Cardiology· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Financial conflict of interest in medical research
Trudo Lemmens, Lori Luther
2008· book-chapter· en· Cambridge University Press eBooks· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · metaresearch+research_integrityconsensus · none
7
citations

How this was built: Screen · Findings · About