MétaCan
ENFR
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.

Export CSVExport JSONAPI query

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
Topic Modeling
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.

2,769 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.
2,769 works in the cohort · of 4,299,418page 22 of 56

Labels cover 6 of 2,769 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 2,769 of 2,769 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
Show us the model
Mark S. Seidenberg, Marc F. Joanisse
2003· review· en· Trends in Cognitive Sciences· Computer Science
distilled prediction:candidate · noneconsensus · none
7
citations
afffundunlabeled
Optimizing Nugget Annotations with Active Learning
Gaurav Baruah, Haotian Zhang, Rakesh Guttikonda, Jimmy Lin, Mark D. Smucker, Olga Vechtomova
2016· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Analyzing Linguistic Complexity and Scientific Impact
Chao Lu, Yi Bu, Xianlei Dong, Jie Wang, Ying Ding, Vincent Larivière +3 more
2019· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
7
citations
affno abstractunlabeled
Natural Language Processing: An Overview
Hessam Amini, Farhood Farahnak, Leila Kosseim
2019· book-chapter· en· WORLD SCIENTIFIC eBooks· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
7
citations
affunlabeled
CBench
Abdelghny Orogat, Isabelle Liu, Ahmed El-Roby
2021· article· en· Proceedings of the VLDB Endowment· Computer Science
distilled prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Are Poetry And Lyrics All That Different?
Abhishek Singhi, Daniel G. Brown
2014· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
7
citations
← previousnext →

How this was built: Screen · Findings · About