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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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Education Methods and Practices
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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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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.

241 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.
241 works in the cohort · of 4,299,418page 4 of 5

Labels cover 0 of 241 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 241 of 241 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.

aboutno affunlabeled
Finding Hope,Vision through Hardship
Y Sylvia
2008· article· en· 中国妇女(英文版)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Canada: A textbook for slow learning children
2015· dissertation· en· University of Southern California Digital Library· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Boom. Tick. Bing! Writing Bodies In.
Susanne Gannon, Diem Chi Nguyen
2010· article· en· LEARNing Landscapes· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
If You Teach Them To Write They Will Read
Feland L. Meadows, Carla Roberto
2016· article· en· European Scientific Journal ESJ· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Effect of Antidepressants on Sleep in Functional Dyspepsia
Yuri A. Saito, Ann E. Almazar, Richard G Locke, Ernest P. Bouras, Colin W. Howden, Brian E. Lacy +12 more
2015· article· en· The American Journal of Gastroenterology· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affvenueno abstractunlabeled
The Look of Silence.
John Roosa, Signe Byrge Sørensen, Errol Morris, Niels Pagh Andersen
2017· article· en· Pacific Affairs· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Learning to Rank
Reda Alhajj, Jon Rokne
2018· book-chapter· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Dear IEJEE Reader
Kamil Özerk
2016· article· en· lnternational Electronic Journal of Elementary Education· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affno abstractunlabeled
Montessori Education in Canada
Margaret D. Whitley
2023· other· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
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How this was built: Screen · Findings · About