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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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Mobile Learning in Education
Retraction
Abstract
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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
aboutaboutness

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

690 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.
690 works in the cohort · of 4,299,418page 8 of 14

Labels cover 2 of 690 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 690 of 690 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Applying CMM Towards an m-Learning Context
Muasaad Alrasheedi, Luiz Fernando Capretz
2015· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
3
citations
fundno affunlabeled
Using NLP to Support English Teaching in Rural Schools
Luis Chiruzzo, Laura Musto, Santiago Góngora, Brian Carpenter, Juan Pablo Filevich, Aiala Rosá
2022· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
3
citations
affunlabeled
A Flexible Learning Framework for Kids
Gregory Petersen, Steven Lyall, Musfiq Rahman
2016· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
3
citations
affvenueunlabeled
Take Out Your Cell Phones - Class is Starting -- Revisited
Jason Bazylak, Susan McCahan, Peter Elliot Weiss, Phil Anderson
2013· article· en· Proceedings of the Canadian Engineering Education Association (CEEA)· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations
affaboutunlabeled
Beyond Mobile Learning
André H. Caron, Letizia Caronia, Pascal Gagné
2010· book-chapter· en· IGI Global eBooks· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · none
2
citations
affunlabeled
Mobile Learning - Student Perspectives
Linda Chmiliar
2010· article· en· AUSpace (Athabasca University)· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Geotrekking: Connecting Education to the Real World
Tim Pelton, Leslee Francis Pelton, Karen Moore
2007· article· en· Society for Information Technology & Teacher Education International Conference· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations
affunlabeled
M-learning activity-based context management
Essa Basaeed, Jawad Berri, Rachid Benlamri, Mohamed Jamal Zemerly
2007· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations
affaboutunlabeled
iPad and iPod in the Language Classrooms
Martine Pellerin
2018· book-chapter· en· Advances in educational technologies and instructional design book series· Computer Science
distilled prediction:candidate · noneconsensus · none
2
citations
venueno affunlabeled
Embodying digital spaces in a clinical encounter
Line Blixt, Kari Nyheim Solbrække, Wenche Schrøder Bjorbækmo
2023· article· en· Phenomenology & Practice· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
2
citations
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How this was built: Screen · Findings · About