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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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Artificial Intelligence in Games
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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.

925 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.
925 works in the cohort · of 4,299,418page 1 of 19

Labels cover 0 of 925 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 925 of 925 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
Cooperative Pathfinding
David Silver
2005· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
665
citations
affunlabeled
Checkers Is Solved
Jonathan Schaeffer, Neil Burch, Yngvi Björnsson, Akihiro Kishimoto, Martin Müller, Robert W. Lake +2 more
2007· article· en· Science· Computer Science
machine prediction:candidate · noneconsensus · none
436
citations
afffundunlabeled
Heads-up limit hold’em poker is solved
Michael Bowling, Neil Burch, Michael Johanson, Oskari Tammelin
2015· article· en· Science· Computer Science
machine prediction:candidate · noneconsensus · none
350
citations
afffundno abstractunlabeled
The challenge of poker
Darse Billings, Aaron Davidson, Jonathan Schaeffer, Duane Szafron
2002· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
271
citations
fundno affno abstractunlabeled
Adaptive game AI with dynamic scripting
Pieter Spronck, Marc Ponsen, I.G. Sprinkhuizen-Kuyper, Eric Postma
2006· article· en· Machine Learning· Computer Science
machine prediction:candidate · noneconsensus · none
260
citations
affno abstractunlabeled
Games solved: Now and in the future
H.J. van den Herik, J.W.H.M. Uiterwijk, Jack van Rijswijck
2002· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
253
citations
affunlabeled
The Hanabi challenge: A new frontier for AI research
Nolan Bard, Jakob Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, Hai-Jing Song +9 more
2019· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
237
citations
affunlabeled
Interactive Storytelling: A Player Modelling Approach
David Thue, Vadim Bulitko, Marcia L. Spetch, Eric Wasylishen
2007· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
200
citations
affno abstractunlabeled
Computer Go
Martin Müller
2002· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
180
citations
affunlabeled
Bayes' Bluff: Opponent Modelling in Poker
Finnegan Southey, Michael Bowling, Bryce Larson, Carmelo Piccione, Neil Burch, Darse Billings +1 more
2012· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
149
citations
affunlabeled
Monte Carlo Tree Search in Hex
Broderick Arneson, Ryan Hayward, Philip Henderson
2010· article· en· IEEE Transactions on Computational Intelligence and AI in Games· Computer Science
machine prediction:candidate · noneconsensus · none
143
citations
affunlabeled
The grand challenge of computer Go
Sylvain Gelly, Levente Kocsis, Marc Schoenauer, Michèle Sébag, David Silver, Csaba Szepesvári +1 more
2012· article· en· Communications of the ACM· Computer Science
machine prediction:candidate · noneconsensus · none
136
citations
affunlabeled
Fast Heuristic Search for RTS Game Combat Scenarios
David G. Churchill, Abdallah Saffidine, Michael Buro
2012· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
122
citations
affunlabeled
Build Order Optimization in StarCraft
David G. Churchill, Michael Buro
2011· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
101
citations
affno abstractunlabeled
Temporal-difference search in computer Go
David Silver, Richard S. Sutton, Martin Müller
2012· article· en· Machine Learning· Computer Science
machine prediction:candidate · noneconsensus · none
93
citations
afffundno abstractunlabeled
Games, computers, and artificial intelligence
Jonathan Schaeffer, H.J. van den Herik
2002· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
74
citations
affunlabeled
Abstraction pathologies in extensive games
Kevin Waugh, David Schnizlein, Michael Bowling, Duane Szafron
2009· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
73
citations
afffundunlabeled
Solving Imperfect Information Games Using Decomposition
Neil Burch, Michael Johanson, Michael Bowling
2014· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
68
citations
affunlabeled
Now You Can Compete With Anyone
Rodrigo Vicencio-Moreira, Regan L. Mandryk, Carl Gutwin
2015· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
68
citations
affunlabeled
Real‐Time Strategy Game Competitions
Michael Buro, David G. Churchill
2012· article· en· AI Magazine· Computer Science
machine prediction:candidate · noneconsensus · none
67
citations
affunlabeled
Computing Robust Counter-Strategies
Michael Johanson, Michael Bowling, Martin Zinkevich
2007· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
67
citations
afffundunlabeled
Finding Optimal Abstract Strategies in Extensive-Form Games
Michael Johanson, Nolan Bard, Neil Burch, Michael Bowling
2021· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
65
citations
affunlabeled
Memory-Efficient Abstractions for Pathfinding
Nathan Sturtevant
2007· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
65
citations
affunlabeled
Emotional Requirements in Video Games
David Callele, Eric Neufeld, Kevin A. Schneider
2006· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
63
citations
afffundno abstractunlabeled
Heuristic Search Applied to Abstract Combat Games
Alexander Kovarsky, Michael Buro
2005· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
63
citations

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