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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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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.

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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.

109 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
109 works in the cohort · of 4,299,418page 2 of 3

Labels cover 0 of 109 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 109 of 109 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.

affno abstractunlabeled
PickPocket: A computer billiards shark
Michael W. Smith
2007· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
31
citations
affno abstractunlabeled
Specifying and computing preferred plans
Meghyn Bienvenu, Christian Fritz, Sheila A. McIlraith
2010· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
30
citations
affno abstractunlabeled
Predicting the size of IDA*ʼs search tree
Levi H. S. Lelis, Sandra Zilles, Robert C. Holte
2013· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
27
citations
affno abstractunlabeled
Probabilistic models for melodic prediction
Jean-François Paiement, Samy Bengio, Douglas Eck
2009· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
17
citations
affno abstractunlabeled
How to progress a database III
Stavros Vassos, Hector J. Levesque
2012· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
afffundno abstractunlabeled
The logic of qualitative probability
James P. Delgrande, Bryan Renne
2019· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
affno abstractunlabeled
Probably bounded suboptimal heuristic search
Roni Stern, Gal Dreiman, Richard Valenzano
2018· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
9
citations
fundno affno abstractunlabeled
Gelfond–Zhang aggregates as propositional formulas
Pedro Cabalar, Jorge Fandinno, Torsten Schaub, Sebastian Schellhorn
2019· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
afffundno abstractunlabeled
The Configurable SAT Solver Challenge (CSSC)
Frank Hutter, Marius Lindauer, Adrian Balint, Sam Bayless, Holger H. Hoos, Kevin Leyton‐Brown
2016· preprint· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affno abstractunlabeled
Probabilistic sentence satisfiability: An approach to PSAT
Tom Henderson, Robert F. Simmons, Bernard Serbinowski, Martin J. Cline, David Sacharny, Xiuyi Fan +1 more
2019· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affno abstractunlabeled
Conflict-tolerant and conflict-free multi-agent meeting
Dor Atzmon, Ariel Felner, Jiaoyang Li, Shahaf Shperberg, Nathan Sturtevant, Sven Koenig
2023· article· en· Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Editorial
Craig Boutilier, Tom Dean, Sven Koenig
2003· editorial· es· Artificial Intelligence
machine prediction:candidate · insufficient_payloadconsensus · none
2
citations
affno abstractunlabeled
Book review
Kevin Murphy
2009· article· en· Artificial Intelligence
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
affno abstractunlabeled
Book review
Yang Xiang
2009· article· en· Artificial Intelligence
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
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