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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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Robotic Path Planning Algorithms
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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.

1,570 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.
1,570 works in the cohort · of 4,299,418page 1 of 32

Labels cover 1 of 1,570 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 1,570 of 1,570 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
Formations of Vehicles in Cyclic Pursuit
Joshua A. Marshall, Mireille E. Broucke, Bruce A. Francis
2004· article· en· IEEE Transactions on Automatic Control· Computer Science
machine prediction:candidate · noneconsensus · none
669
citations
affunlabeled
Computational Principles of Mobile Robotics
Gregory Dudek, Michael Jenkin
2010· book· en· Cambridge University Press eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
654
citations
affunlabeled
Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks
Roni Stern, Nathan Sturtevant, Ariel Felner, Sven Koenig, Hang Ma, Thayne T. Walker +6 more
2021· preprint· en· Proceedings of the International Symposium on Combinatorial Search· Computer Science
machine prediction:candidate · noneconsensus · none
276
citations
afffundunlabeled
Crash Mitigation in Motion Planning for Autonomous Vehicles
Hong Wang, Yanjun Huang, Amir Khajepour, Yubiao Zhang, Yadollah Rasekhipour, Dongpu Cao
2019· article· en· IEEE Transactions on Intelligent Transportation Systems· Computer Science
machine prediction:candidate · noneconsensus · none
253
citations
fundno affno abstractunlabeled
Motion planning for formations of mobile robots
Tim Barfoot, Christopher M. Clark
2004· article· en· Robotics and Autonomous Systems· Computer Science
machine prediction:candidate · noneconsensus · none
204
citations
afffundunlabeled
Voronoi diagram in optimal path planning
Priyadarshi Bhattacharya, Marina L. Gavrilova
2007· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
141
citations
affunlabeled
Bounding on rough terrain with the LittleDog robot
Alexander Shkolnik, Michael Levashov, Ian R. Manchester, Russ Tedrake
2010· article· en· The International Journal of Robotics Research· Computer Science
machine prediction:candidate · noneconsensus · none
126
citations
affno abstractunlabeled
Real-time safety for human–robot interaction
Dana Kulić, Elizabeth A. Croft
2005· article· en· Robotics and Autonomous Systems· Computer Science
machine prediction:candidate · noneconsensus · none
111
citations

How this was built: Screen · Findings · About