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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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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 2 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
Recent Work in Connectivism
Stephen Downes
2020· article· fr· European Journal of Open Distance and E-Learning· Computer Science
machine prediction:candidate · noneconsensus · none
133
citations
affunlabeled
Learning Analytics for Self-Regulated Learning
Philip H. Winne
2017· book-chapter· en· Society for Learning Analytics Research (SoLAR) eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
133
citations
venueno affunlabeled
Understanding Learners’ Motivation and Learning Strategies in MOOCs
Carlos Alario‐Hoyos, Iria Estévez Ayres, Mar Pérez‐Sanagustín, Carlos Delgado Kloos, Carmen Fernández-Panadero
2017· article· en· The International Review of Research in Open and Distributed Learning· Computer Science
machine prediction:candidate · noneconsensus · none
131
citations
affunlabeled
Penetrating the black box of time-on-task estimation
Vitomir Kovanović, Dragan Gašević, Shane Dawson, Srécko Joksimovíc, Ryan S. Baker, Marek Hatala
2015· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
119
citations
affvenueunlabeled
Elements of Open Education: An Invitation to Future Research
Olaf Zawacki‐Richter, Dianne Conrad, Aras Bozkurt, Cengiz Hakan Aydın, Svenja Bedenlier, Insung Jung +19 more
2020· article· en· The International Review of Research in Open and Distributed Learning· Computer Science
machine prediction:candidate · open_scienceconsensus · none
106
citations
affno abstractunlabeled
Exploring communities of inquiry in Massive Open Online Courses
Vitomir Kovanović, Srécko Joksimovíc, Oleksandra Poquet, Thieme Hennis, Iva Čukić, P. de Vries +4 more
2017· article· en· Computers & Education· Computer Science
machine prediction:candidate · noneconsensus · none
99
citations
aboutno affunlabeled
Digital resilience in higher education
Martin Weller, Terry Anderson
2013· article· en· Open Research Online (The Open University)· Computer Science
machine prediction:candidate · noneconsensus · none
99
citations
affunlabeled
Student success system
Alfred Essa, Hanan Ayad
2012· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
93
citations
affunlabeled
What if learning analytics were based on learning science?
Zahia Marzouk, Mladen Raković, Amna Liaqat, Jovita Vytasek, Donya Samadi, Jason Stewart-Alonso +4 more
2016· article· en· Australasian Journal of Educational Technology· Computer Science
machine prediction:candidate · noneconsensus · none
87
citations
venueno affunlabeled
A Taxonomy of Asynchronous Instructional Video Styles
Konstantinos Chorianopoulos
2018· article· en· The International Review of Research in Open and Distributed Learning· Computer Science
machine prediction:candidate · noneconsensus · none
84
citations

How this was built: Screen · Findings · About