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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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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.

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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 22 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 teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Massive Open Online Courses in China
Xiaobin Li
2019· book-chapter· en· Advances in educational technologies and instructional design book series· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
1
citations
affunlabeled
How big data is used as a key element for hybrid university education
Herbert Víctor Huaranga Rivera, Milca Betsabé Herrera Aponte, José L. Gonzáles, Milagros del Rosario Cáceres Chávez, Katherinne Diana Magaly Itusaca Cahua, Christian Paolo Martel Carranza
2022· article· en· International Journal of Health Sciences· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
Extrinsic and Intrinsic for online Classroom
Yuwanuch Gulatee, Babara Combes, Yuwadee Yoosabai, Piyaphisak Jaerasukon
2021· article· en· Higher Education Studies· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Learning Analytics in a Blended Learning Context
Mike Carbonaro, Amanda P. Montgomery, Amin Mousavi, Bill Dunn, Denyse V. Hayward
2017· article· en· EdMedia: World Conference on Educational Media and Technology· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Co-Constructing Knowledge Through mOOC Design and Development
Laura Morrison, Diana Petrarca, Janette Hughes, Jennifer Laffier
2015· article· en· Society for Information Technology & Teacher Education International Conference· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Using Deep Learning to Localize Errors in Student Code Submissions
Shion Fujimori, Mohamed Harmanani, Owais Siddiqui, Lisa Zhang
2022· article· en· Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2· Computer Science
distilled prediction:candidate · open_scienceconsensus · none
1
citations
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