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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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Innovations in Educational Methods
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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.

427 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.
427 works in the cohort · of 4,299,418page 3 of 9

Labels cover 1 of 427 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 427 of 427 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
On Online Assignments in a Calculus Class
Veselin Jungić, Deborah Kent, Petra Menz
2012· article· en· Journal of University Teaching and Learning Practice· Social Sciences
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
The Economics Instructor's Toolbox
Julien Picault
2019· article· en· SSRN Electronic Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Introduction to the Utility Foundations of Kelly
Leonard C. MacLean, Edward O. Thorp, William T. Ziemba
2011· book-chapter· en· World Scientific handbook in financial economic series· Social Sciences
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
To Repeat or Not to Repeat a Course
Michael J. Armstrong, Ernest N. Biktimirov
2013· article· en· Journal of Education for Business· Social Sciences
machine prediction:candidate · noneconsensus · none
6
citations
venueno affunlabeled
Lecture Capture: Friend or Foe?
Alison Reid, D. Duret, Karen Noble
2021· article· en· Journal of Veterinary Medical Education· Social Sciences
machine prediction:candidate · noneconsensus · none
5
citations
aboutno affunlabeled
Teaching-Track Economists in the United Kingdom
Fabio Aricò, Alvin Birdi, Caroline Elliott, Cloda Jenkins, Ashley Lait, Christian Spielmann
2024· article· en· AEA Papers and Proceedings· Social Sciences
machine prediction:candidate · metaresearchconsensus · none
4
citations
fundno affunlabeled
Incentives in On‐line Education
Paul Oslington
2005· article· en· Journal of Higher Education Policy and Management· Social Sciences
machine prediction:candidate · noneconsensus · none
4
citations
affvenueno abstractunlabeled
Up and running online
Josephine Esther Sciortino, D. Robert Siemens
2013· article· en· Canadian Urological Association Journal· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
4
citations
affunlabeled
Can Business Students Forecast Their Own Grade?
Belayet Hossain, Panagiotis Tsigaris
2012· article· en· American Journal of Business Education (AJBE)· Social Sciences
machine prediction:candidate · noneconsensus · none
4
citations
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How this was built: Screen · Findings · About