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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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Foundations and Trends® in Machine Learning
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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.

7 results · 1 filter active ·
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20092025
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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.
7 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 7 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 7 of 7 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.

affno abstractunlabeled
Learning Deep Architectures for AI
Yoshua Bengio
2009· article· en· Foundations and Trends® in Machine Learning· Computer Science
machine prediction:candidate · noneconsensus · none
6,910
citations
affunlabeled
An Introduction to Deep Reinforcement Learning
Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joëlle Pineau
2018· article· en· Foundations and Trends® in Machine Learning· Computer Science
machine prediction:candidate · noneconsensus · none
1,251
citations
affunlabeled
A Survey of Statistical Network Models
Anna Goldenberg
2010· article· en· Foundations and Trends® in Machine Learning· Physics and Astronomy
machine prediction:candidate · noneconsensus · none
853
citations
affunlabeled
Bayesian Reinforcement Learning: A Survey
Mohammed Ghavamzadeh, Shie Mannor, Joëlle Pineau, Aviv Tamar
2015· article· en· Foundations and Trends® in Machine Learning· Computer Science
machine prediction:candidate · noneconsensus · none
223
citations

How this was built: Screen · Findings · About