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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.

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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
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.

980 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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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 11 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.

affunlabeled
What comes after CS 1 + 2
Troy Vasiga
2002· article· en· ACM SIGCSE Bulletin· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affvenueunlabeled
From Computational Thinking to Political Resistance
Rouhollah Aghasaleh, Patrick Enderle, Anton Puvirajah
2019· article· en· Journal for Activist Science and Technology Education· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Deploying an Educational Mobile Robot
Dorina Plókai, Borsa Détár, Tamás Haidegger, Enikő Nagy
2025· article· en· Machines· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Technology in University Mathematics Education
Carl Winsløw, Marianna Bosch, Alejandro S. González-Martín, Rongrong Huo
2023· book-chapter· en· Springer international handbooks of education· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
RAPT
Olessia Karpova, Noel D’Souza, Diane Horton, Andrew Petersen
2015· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
2
citations
affaboutunlabeled
Integrating Computational Thinking and Mathematics
Marja Gabrielle Bertrand, Immaculate Kizito Namukasa
2019· book-chapter· en· Advances in educational technologies and instructional design book series· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Values and Beliefs Underpinning K-12 Computing Education
Carsten Schulte, Sue Sentance, Sören Sparmann, Rukiye Altın, Mor Friebroon‐Yesharim, Martina Landman +9 more
2024· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Understanding abstraction
Celina Gibbs, Yvonne Coady
2010· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Assessment in the Makerspace
Janette Hughes, Stephanie Thompson
2022· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
GameSoup
Kevin Tonon, Ronald M. Baecker
2010· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
The CS Concept Inventory Quiz Show
Nafeesa Dewji, Steven A. Wolfman, Geoffrey Herman, Leo Porter, Cynthia Taylor, Jan Vahrenhold
2015· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Gentlemen, Start Your Engines
Jonathan Schaeffer
2008· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
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