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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.

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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
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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

1,694 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
1,694 works in the cohort · of 4,299,418page 27 of 34

Labels cover 10 of 1,694 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 1,694 of 1,694 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.

venueno affunlabeled
Message from the Editor-in-Chief
Ingrid Harrington
2025· article· en· International Journal of Higher Education· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
AI-Enhanced Learning and Teacher Productivity
Omniah AlQahtani
2025· book-chapter· en· Advances in computational intelligence and robotics book series· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
On College Blended Learning Based on MOOC
Xiaoli Bao
2016· article· en· Higher education of social science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
Practices and Beliefs about Educational Data Usage
Ajay Sivanand, Brian Frank
2018· article· en· Proceedings of the Canadian Engineering Education Association (CEEA)· Computer Science
machine prediction:candidate · metaresearchconsensus · none
0
citations
affunlabeled
Bringing Web 2.0 into the Learning Environment
Saman Shahryari Monfared, Peyman Ajabi-Naeini, Drew Parker
2013· book-chapter· en· IGI Global eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
10.3991/ijet.v19i02.47223
Xuecheng Wu
2000· article· en· Time to knit· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Essential MySQL Skills
Thomas Valentine
2023· book-chapter· en· Apress eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Personalized Student Attribute Inference
Khalid Moustapha Askia, Marie‐Jean Meurs
2020· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
A Framework for MOOC Content Generation
Kanmanus Ongvisatepaiboon, Jonathan H. Chan
2018· article· en· Proceedings of the Canadian Engineering Education Association (CEEA)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Editorial Acknowledgment
2024· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
AI skills and capabilities in Canada
Diego Eslava, Fabio Manca, Caroline Paunov
2025· report· en· OECD artificial intelligence papers· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About