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 11 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.

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 affno abstractunlabeled
The Canadian Journal of Addiction
Nady el‐Guebaly
2013· article· en· The Canadian Journal of Addiction· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · insufficient_payloadconsensus · none
7
citations
aboutno affunlabeled
Experiences with patient charges
Flora M. Haaijer‐Ruskamp
2002· article· en· International Journal of Risk & Safety in Medicine· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
6
citations
venueaboutno affunlabeled
Canadian faculties of medicine not in denial
Nick Busing
2011· letter· en· Canadian Medical Association Journal· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
6
citations
venueno affunlabeled
Covert pharmaceutical promotion in free medical journals
Aaron S. Kesselheim
2011· letter· en· Canadian Medical Association Journal· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · metaresearch+research_integrityconsensus · none
6
citations
affunlabeled
Continuing Medical Education
Todd Dorman, Ivan Silver
2011· letter· en· Archives of Internal Medicine· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · insufficient_payloadconsensus · none
6
citations
affunlabeled
Author Conflict and Bias in Research
Alexander R. Vaccaro, Alpesh A. Patel, Charles Fisher
2011· review· en· Spine· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · metaresearch+research_integrityconsensus · none
6
citations
aboutno affunlabeled
The pharma deals that CCGs fail to declare
Tom Moberly
2018· article· en· BMJ· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · research_integrityconsensus · none
6
citations
affno abstractunlabeled
Depressing research
Daniel Roth, Erin C. Boyle, Darcy Beer, Anita Malik, Jen deBruyn
2004· letter· en· The Lancet· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · noneconsensus · none
6
citations
afffundaboutunlabeled
The Costs of Industry-Sponsored Drug Trials in Canada
Dat T. Tran, İlke Akpinar, Philip Jacobs
2019· article· en· PharmacoEconomics - Open· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · metaresearchconsensus · none
6
citations
affgemma · metaresearch+research_integritygpt · metaresearch+research_integritymodels agree
Research on policy mechanisms to address funding bias and conflicts of interest in biomedical research: a scoping review
S. Scott Graham, Quinn Grundy, Nandini Sharma, Joshua B. Barbour, Justin F. Rousseau, Zoltan P. Majdik +1 more
2025· review· en· Research Integrity and Peer Review· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · metaresearch+research_integrityconsensus · metaresearch
6
citations
affaboutunlabeled
Correcting the record on NCRG‐funded research
Linda B. Cottler, Tammy Chung, David C. Hodgins, Miriam Jorgensen, Gloria M. Miele
2016· letter· en· Addiction· Pharmacology, Toxicology and Pharmaceutics
machine prediction:candidate · research_integrityconsensus · none
6
citations

How this was built: Screen · Findings · About