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
Research Data Management Practices
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.

2,427 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.
2,427 works in the cohort · of 4,299,418page 28 of 49

Labels cover 37 of 2,427 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 2,427 of 2,427 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.

fundno affunlabeled
Attention please!
2018· article· en· Econstor (Econstor)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affgemma · metaresearchgpt · metaresearch+scholarly_communicationmodels split
Altmetrics Data Quality Code of Conduct
2016· article· en· Lincoln (University of Nebraska)· Computer Science
machine prediction:candidate · metaresearch+bibliometricsconsensus · metaresearch
0
citations
affunlabeled
GreenFILE
Jane Duffy
2024· article· en· The Charleston Advisor· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affgemma · open_sciencegpt · open_sciencemodels agree
Teaching Open Science
Lorne Campbell
2015· dataset· en· The Winnower· Computer Science
machine prediction:candidate · open_scienceconsensus · none
0
citations
aboutno affunlabeled
Evaluating In Vitro Distribution Models
2024· other· en· U.S. Environmental Protection Agency· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Book Reviews
Janet Halsall, Pippa Smart, Anthony Watkinson
2004· article· en· Learned Publishing· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
“Business as Usual,” But What Is Usual?
J.F. Devlin, Neil R. Thomson
2021· article· en· Groundwater Monitoring & Remediation· Computer Science
machine prediction:candidate · metaresearchconsensus · none
0
citations
affunlabeled
President's Page
Nadia Caidi
2016· article· en· Bulletin of the Association for Information Science and Technology· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Thank You to Our 2023 Reviewers
Alexandre Schubnel, Rachel E. Abercrombie, Yves Bernabé, M. G. Bostock, Mark J. Dekkers, Anke Friedrich +6 more
2024· article· en· Journal of Geophysical Research Solid Earth· Computer Science
machine prediction:candidate · metaresearchconsensus · none
0
citations
venueaboutno affunlabeled
Welcome from the CAIS/ACSI 2016 Conference Co-Chairs
David Michels, Angela Pollak
2016· article· fr· Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueaboutno affunlabeled
The Edges of Institutional Repositories
Bar Fridman-Tell, Zoë Gavin, C. Davidson, Michelle Pettis
2025· article· The iJournal Student Journal of the Faculty of Information· Computer Science
machine prediction:candidate · scholarly_communicationconsensus · none
0
citations
aboutno affno abstractunlabeled
Ontario, Niagara Falls
2010· other· nl· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affvenueaboutunlabeled
AI in Canadian LIS Journals
Emily Kroeker, Gail M. Thornton
2025· article· fr· Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About