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
Intelligent Tutoring Systems and Adaptive Learning
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.

789 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.
789 works in the cohort · of 4,299,418page 6 of 16

Labels cover 1 of 789 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 789 of 789 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
Impact of Decoding Work within a Professional Program
Michelle Yeo, Mark R. Lafave, Khatija Westbrook, Jenelle McAllister, Dennis Valdez, Breda Eubank
2017· article· en· New Directions for Teaching and Learning· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Call with Current Continuation Patterns
Darrell Ferguson, Dwight Deugo
2001· article· en· The Angle Orthodontist· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affno abstractunlabeled
QuizMaster: An Adaptive Formative Assessment System
Fuhua Lin, Raymond Morland, Hongxin Yan
2024· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Working Memory and Language
John W. Schwieter, Zhisheng Wen, Teresa Bennett
2022· book-chapter· en· Cambridge University Press eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Visualising Uncertainty for Open Learner Model Users.
Carrie Demmans Epp, Susan Bull, Matthew D. Johnson
2014· article· en· University of Birmingham Research Portal (University of Birmingham)· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Artificial Intelligence: The Views of Tertiary-Level Foreign Language Learners
Mariane Gazaille, Dana Di Pardo Léon-Henri, Andréanne L. Nolin, Noémie Gendron Perrault
2022· book-chapter· en· Advances in Social Science, Education and Humanities Research/Advances in social science, education and humanities research· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations

How this was built: Screen · Findings · About