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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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venuejournal
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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 29 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.

affunlabeled
PACMHCI V8, CSCW1, April 2024 Editorial
Munmun De Choudhury, Xianghua Ding, Shion Guha, Aparecido Fabiano Pinatti de Carvalho, Daniel Cardoso Llach, Maryam Mustafa +2 more
2024· article· en· Proceedings of the ACM on Human-Computer Interaction· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
fundno affno abstractunlabeled
Knowledge Translation and Transfer Plan
Jean Knowlton
2014· article· en· The Atrium (University of Guelph)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
CLASSROOM ON DEMAND: FAST AND FRESH VIDEO CONTENT GENERATOR
Prasert Kanthamanon, Wichian Chutimaskul, Vajirasak Vanijja
2018· article· en· Proceedings of the Canadian Engineering Education Association (CEEA)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
A Systematic Comparative Analysis of MOOC Participant Profiles
Bruno Poëllhuber, Normand Roy, Ibtihel Bouchoucha
2015· article· en· E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
The Nature of DeepSeek Used in Teaching
2025· article· en· Journal of Artificial Intelligence Practice· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
SIGCSE Technical Symposium 2022
Leen‐Kiat Soh, Brian Dorn, Lina Battestilli
2022· article· en· ACM SIGCSE Bulletin· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affvenueaboutunlabeled
Les MOOC dans les universités québécoises
Mélanie Julien, Lynda Gosselin
2016· article· fr· Revue internationale des technologies en pédagogie universitaire· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
AI FOR EDUCATIONAL CONTENT CREATION
2024· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
D4.1: Interim PRACE Training Report
2020· article· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Quality of Online Learning: Adding MOOC into the mix?
Afsaneh Sharif, Hosein Moeini, Mercé Gisbert Cervera
2013· article· en· EdMedia: World Conference on Educational Media and Technology· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Challenge and Response Analysis for MOOCs
Huan Xu
2015· article· en· Higher education of social science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About