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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.

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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 34 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
De Lausanne à Yaoundé : l’aventure des MOOCs
Dimitrios Noukakis, Gérard Escher, Patrick Aebischer
2016· article· fr· Annales des Mines - Réalités industrielles· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
AI in Higher Education: A CLARIN Community Survey
Iulianna van der Lek-Ciudin, Anna Woldrich, Tanja Wissik
2025· article· en· Digital Humanities in the Nordic and Baltic Countries Publications· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Learning Analytics and xAPI.pdf
David Topps, Ellen Meiselman
2019· dataset· en· Harvard Dataverse· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Koli Calling 2021 report
Andrew Petersen, Otto Seppälä
2022· article· en· ACM SIGCSE Bulletin· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations

How this was built: Screen · Findings · About