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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
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.

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 3 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
Predicting Army Combat Outcomes in StarCraft
Marius Stănescu, Sergio Poo Hernandez, Graham Erickson, Russel Greiner, Michael Buro
2013· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
34
citations
affunlabeled
Generalized amazons is PSPACE-complete
Timothy Furtak, Masashi Kiyomi, Takeaki Uno, Michael Buro
2005· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
34
citations
affunlabeled
Using Lanchester Attrition Laws for Combat Prediction in StarCraft
Marius Stănescu, Nicolas A. Barriga, Michael Buro
2015· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
32
citations
affunlabeled
Global State Evaluation in StarCraft
Graham Erickson, Michael Buro
2014· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
32
citations
affunlabeled
Simultaneous Dual Level Creation for Games
Daniel Ashlock, Colin Lee, Cameron McGuinness
2011· article· en· IEEE Computational Intelligence Magazine· Computer Science
machine prediction:candidate · noneconsensus · none
32
citations
affno abstractunlabeled
PickPocket: A computer billiards shark
Michael W. Smith
2007· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
31
citations
afffundunlabeled
Action Abstractions for Combinatorial Multi-Armed Bandit Tree Search
Rubens O. Moraes, Julián P. Mariño, Levi H. S. Lelis, Mário A. Nascimento
2018· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
30
citations
affunlabeled
Biased Cost Pathfinding
Alborz Geramifard, Pirooz Chubak, Vadim Bulitko
2006· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
30
citations
afffundunlabeled
Active Goal Recognition
Maayan Shvo, Sheila A. McIlraith
2020· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
30
citations
affno abstractunlabeled
The complexity of zero-visibility cops and robber
Dariusz Dereniowski, Danny Dyer, Ryan M. Tifenbach, Boting Yang
2015· article· en· Theoretical Computer Science· Computer Science
machine prediction:candidate · noneconsensus · none
27
citations
affunlabeled
Incorporating Search Algorithms into RTS Game Agents
David G. Churchill, Michael Buro
2012· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
27
citations
afffundunlabeled
The Game of End-Nim
Michael Albert, Richard J. Nowakowski
2001· article· en· The Electronic Journal of Combinatorics· Computer Science
machine prediction:candidate · noneconsensus · none
26
citations
afffundunlabeled
Using Response Functions to Measure Strategy Strength
Trevor Davis, Neil Burch, Michael Bowling
2014· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
26
citations
affno abstractunlabeled
Multi-cut αβ-pruning in game-tree search
Yngvi Björnsson, T.A. Marsland
2001· article· en· Theoretical Computer Science· Computer Science
machine prediction:candidate · noneconsensus · none
26
citations
affunlabeled
Emotional Requirements
David Callele, Eric Neufeld, Kevin A. Schneider
2008· article· en· IEEE Software· Computer Science
machine prediction:candidate · noneconsensus · none
26
citations
affunlabeled
Recommender System for Items in <i>Dota 2</i>
Wenli Looi, Manmeet Dhaliwal, Reda Alhajj, Jon Rokne
2018· article· en· IEEE Transactions on Games· Computer Science
machine prediction:candidate · noneconsensus · none
25
citations
affunlabeled
Another bridge between NIM and WYTHOFF
Éric Duchêne, Aviezri S. Fraenkel, Sylvain Gravier, Richard J. Nowakowski
2009· preprint· en· Computer Science
machine prediction:candidate · noneconsensus · none
24
citations
affunlabeled
Learning to play strong poker
Darse Billings, Lourdes Peña‐Castillo, Jonathan Schaeffer, Duane Szafron
2001· book· en· Nova Science Publishers, Inc. eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
24
citations
afffundunlabeled
Alpha-Beta Pruning for Games with Simultaneous Moves
Abdallah Saffidine, Hilmar Finnsson, Michael Buro
2021· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
23
citations
afffundunlabeled
Evaluating strategies for running from the cops
Carsten Moldenhauer, Nathan Sturtevant
2009· article· en· Infoscience (Ecole Polytechnique Fédérale de Lausanne)· Computer Science
machine prediction:candidate · noneconsensus · none
22
citations
affunlabeled
Dynamic One-Pile Nim
Arthur Holshouser, Harold Reiter, James Rudzinski
2003· article· en· ˜The œFibonacci quarterly· Computer Science
machine prediction:candidate · noneconsensus · none
22
citations
afffundunlabeled
An Exploration Tool for Predicting Stealthy Behaviour
Jonathan Tremblay, Pedro J. Rivera Torres, Nir Rikovitch, Clark Verbrugge
2013· article· en· Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment· Computer Science
machine prediction:candidate · noneconsensus · none
22
citations
affunlabeled
Lookahead Pathology in Real-Time Path-Finding.
Vadim Bulitko, Mitja Luštrek
2006· article· en· National Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
22
citations
affno abstractunlabeled
Solving Hex: Beyond Humans
Broderick Arneson, Ryan Hayward, Philip Henderson
2011· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
22
citations

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