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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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Teaching and Learning Programming
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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
fundfunder
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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.

980 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.
980 works in the cohort · of 4,299,418page 6 of 20

Labels cover 2 of 980 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 980 of 980 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.

affno abstractunlabeled
Developing Technopedagogical Skills in Pre-service Teachers
Lorraine Beaudin, Corey Hadden
2004· article· en· E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
aboutno affunlabeled
Re-Making Teacher Professional Development
Janette Hughes, Laura Morrison, Laura Doboş
2018· article· en· Studies in health technology and informatics· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
The Impact of Optional Groups on Students
Jonathan Calver, Jennifer Campbell, Michelle Craig, Jonathan Lam
2022· article· en· Proceedings of the 53rd ACM Technical Symposium on Computer Science Education· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
afffundunlabeled
Thinking with hands
Alissa N. Antle, Milena Droumeva, Daniel Ha
2009· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Modern goto
Stewart D. Smith, Nicholas Zemljic, Andrew Petersen
2015· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Benchmarking Introductory Programming Exams
Judy Sheard, Daryl D’Souza, Peter Klemperer, Leo Porter, Juha Sorva, Martijn Stegeman +1 more
2016· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
First Principles of CS Instruction
Katrin Becker
2006· article· en· Open MIND· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Following a thread
Michelle Craig, Sarah C. Petersen, Andrew Petersen
2012· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Cognitive Apprenticeship and Artificial Intelligence Coding Assistants
Eric Poitras, Brent Crane, David Dempsey, Tavis A. Bragg, Angela A. Siegel, Michael Pin-Chuan Lin
2024· book-chapter· en· Advances in educational technologies and instructional design book series· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Benchmarking Introductory Programming Exams
Judy Sheard, Daryl D’Souza, Peter Klemperer, Leo Porter, Juha Sorva, Martijn Stegeman +1 more
2016· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
Young Children, Mathematics, and Coding
George Gadanidis
2014· book-chapter· en· Advances in educational technologies and instructional design book series· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations

How this was built: Screen · Findings · About