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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
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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 20 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
Dynamic Programming Algorithms
2024· book-chapter· en· Cambridge University Press eBooks· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affno abstractunlabeled
Reinforcement Learning Theory
Philip Osborne, Kajal Singh, Matthew E. Taylor
2022· book-chapter· en· Synthesis lectures on artificial intelligence and machine learning· Computer Science
distilled prediction:candidate · metaepi_narrow+sts+research_integrity+insufficient_payloadconsensus · none
0
citations
fundno affunlabeled
Maximum Entropy Model Correction in Reinforcement Learning
Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh, Amir‐massoud Farahmand
2023· preprint· en· PolyPublie (École Polytechnique de Montréal)· Computer Science
distilled prediction:candidate · metaepi_narrow+research_integrityconsensus · none
0
citations
fundno affunlabeled
Toward Open-ended Embodied Tasks Solving
William Wei Wang, Dongqi Han, Xufang Luo, Yifei Shen, Charles X. Ling, Boyu Wang +1 more
2023· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrow+open_science+insufficient_payloadconsensus · open_science
0
citations
affunlabeled
Quasi deterministic POMDPs and DecPOMDPs
Camille Besse, Brahim Chaib-draa
2010· article· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
0
citations
affno abstractunlabeled
Moving beyond reward prediction errors
Blake A. Richards
2019· article· en· Nature Machine Intelligence· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Planning with Expectation Models for Control
Katya Kudashkina, Yi Wan, Abhishek Naik, Richard S. Sutton
2021· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
Efficient planning in R-max
Marek Grześ, Jesse Hoey
2011· article· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Augmented Q Imitation Learning (AQIL)
Xiaolei Zhang, Anish Agarwal
2020· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affno abstractunlabeled
Model-Based Least-Squares Policy Evaluation
Fletcher Lu, Dale Schuurmans
2003· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
Scythe AI: A Tool for Modular Reuse of Game AI
Christopher Dragert, Jörg Kienzle, Clark Verbrugge
2013· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Investigation of Maximization Bias in Sarsa Variants
Ganesh Tata, Eric M. Austin
2021· article· en· 2021 IEEE Symposium Series on Computational Intelligence (SSCI)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
Average-Reward Learning and Planning with Options
Yi Wan, Abhishek Naik, Richard S. Sutton
2021· article· en· Neural Information Processing Systems· Computer Science
distilled prediction:candidate · scholarly_communicationconsensus · none
0
citations
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