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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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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
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.

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 22 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
Signals and Systems OER Labs
2024· other· en· Zenodo (CERN European Organization for Nuclear Research)· Computer Science
distilled prediction:candidate · scholarly_communication+insufficient_payloadconsensus · insufficient_payload
0
citations
afffundunlabeled
Flow Factorization for Efficient Generative Flow Networks
Jiashun Liu, Chunhui Li, Chenghao Liu, Dianbo Liu, Qingpeng Cai, Ling Pan
2025· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Incrementally Learning Functions of the Return
Brendan Bennett, Wesley Chung, Muhammad Zaigham Zaheer, Vincent Liu
2019· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Inequity Aversion Toward AI Counterparts
Debanjan Borthakur, Peter Diep, Jason E. Plaks
2025· preprint· en· Research Square· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+open_science+research_integrityconsensus · none
0
citations
affunlabeled
Evaluation of Techniques for Sim2Real Reinforcement Learning
Mahesh Ranaweera, Qusay H. Mahmoud
2023· article· en· Proceedings of the ... International Florida Artificial Intelligence Research Society Conference· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Deep Double Q-learning
Prabhat Nagarajan, Martha White, Marlos C. Machado
2025· preprint· en· ArXiv.org· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
Approximate Multi-Agent Fitted Q Iteration.
Antoine Lesage‐Landry, Duncan S. Callaway
2021· preprint· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affno abstractunlabeled
Background and Definitions
Philip Osborne, Kajal Singh, Matthew E. Taylor
2022· book-chapter· en· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
0
citations

How this was built: Screen · Findings · About