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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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Reinforcement Learning in Robotics
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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
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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.

1,145 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.
1,145 works in the cohort · of 4,299,418page 21 of 23

Labels cover 2 of 1,145 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 1,145 of 1,145 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Deterministic Planning
2023· book-chapter· en· Cambridge University Press eBooks· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affno abstractunlabeled
Hydrolysate Untargeted Metabolomics Mass Spectrometry Data
2024· dataset· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
distilled prediction:candidate · metaepi_narrow+sts+scholarly_communication+open_science+insufficient_payloadconsensus · open_science+insufficient_payload
0
citations
afffundunlabeled
Low-Rank Representation of Reinforcement Learning Policies
Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joëlle Pineau, Doina Precup +1 more
2022· article· en· Journal of Artificial Intelligence Research· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Multiagent Systems
2023· book-chapter· en· Cambridge University Press eBooks· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
Reasoning and Planning with Certainty
2023· book-chapter· en· Cambridge University Press eBooks· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affno abstractunlabeled
Why AI and Security?
Dilli Prasad Sharma, Arash Habibi Lashkari, Mahdi Daghmehchi Firoozjaei, Samaneh Mahdavifar, Pulei Xiong
2025· book-chapter· en· Progress in IS· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Learning to Optimize Entropy in the Soft Actor-Critic
Zhilei Zhou, Malcolm I. Heywood
2025· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+open_scienceconsensus · none
0
citations
affgemma · no categorygpt · no categorymodels agree
Understanding the Effect of Stochasticity in Policy Optimization
Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans
2021· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
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