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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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Constraint Satisfaction and Optimization
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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.

698 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.
698 works in the cohort · of 4,299,418page 1 of 14

Labels cover 0 of 698 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 698 of 698 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.

afffundunlabeled
ParamILS: An Automatic Algorithm Configuration Framework
Frank Hutter, Holger H. Hoos, Kevin Leyton‐Brown, T. Stuetzle
2009· article· en· Journal of Artificial Intelligence Research· Computer Science
machine prediction:candidate · noneconsensus · none
868
citations
affunlabeled
SATzilla: Portfolio-based Algorithm Selection for SAT
Lizhong Xu, Frank Hutter, Holger H. Hoos, Kevin Leyton‐Brown
2008· article· en· Journal of Artificial Intelligence Research· Computer Science
machine prediction:candidate · noneconsensus · none
835
citations
affunlabeled
Interval arithmetic
Timothy J. Hickey, Qun Ju, M. H. van Emden
2001· article· en· Journal of the ACM· Computer Science
machine prediction:candidate · noneconsensus · none
339
citations
affunlabeled
SATLIB: An Online Resource for Research on SAT
Holger H. Hoos, Thomas Stützle, Ian P. Gent, Hans van Maaren, Toby Walsh
2000· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
312
citations
affunlabeled
A Better Bound on the Variance
Rajendra Bhatia, Chandler Davis
2000· article· en· American Mathematical Monthly· Computer Science
machine prediction:candidate · noneconsensus · none
214
citations
affno abstractunlabeled
Frozen development in graph coloring
Joseph Culberson, Ian P. Gent
2001· article· en· Theoretical Computer Science· Computer Science
machine prediction:candidate · noneconsensus · none
117
citations
affunlabeled
Generalized nogoods in CSPs
George Katsirelos, Fahiem Bacchus
2005· article· en· National Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
84
citations
affno abstractunlabeled
Rigorous results for random (2+p)-SAT
Dimitris Achlioptas, Lefteris M. Kirousis, Evangelos Kranakis, Danny Kriz̧anc
2001· article· en· Theoretical Computer Science· Computer Science
machine prediction:candidate · noneconsensus · none
83
citations
affunlabeled
Learning to solve QBF
Horst Samulowitz, Roland Memisevic
2007· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
80
citations
affno abstractunlabeled
Investigations on autark assignments
Oliver Kullmann
2000· article· en· Discrete Applied Mathematics· Computer Science
machine prediction:candidate · noneconsensus · none
75
citations
afffundunlabeled
Conflict-Directed Backjumping Revisited
Xinguang Chen, Peter van Beek
2001· article· en· Journal of Artificial Intelligence Research· Computer Science
machine prediction:candidate · noneconsensus · none
74
citations
affno abstractunlabeled
Random Constraint Satisfaction: A More Accurate Picture
Dimitris Achlioptas, Michael Molloy, Lefteris M. Kirousis, Yannis C. Stamatiou, Evangelos Kranakis, Danny Kriz̧anc
2001· article· en· Constraints· Computer Science
machine prediction:candidate · noneconsensus · none
68
citations
afffundunlabeled
Near Sets: An Introduction
James F. Peters
2013· article· en· Mathematics in Computer Science· Computer Science
machine prediction:candidate · noneconsensus · none
67
citations
affno abstractunlabeled
The complexity of constraint satisfaction games and QCSP
Ferdinand Börner, А. А. Булатов, H. Chen, Peter Jeavons, Andrei Krokhin
2009· article· en· Information and Computation· Computer Science
machine prediction:candidate · noneconsensus · none
62
citations
affno abstractunlabeled
Temporal Granularity: Completing the Puzzle
Iqbal A. Goralwalla, Yuri Leontiev, M. TAMER ÖZSU, Duane Szafron, Carlo Combi
2001· article· en· Journal of Intelligent Information Systems· Computer Science
machine prediction:candidate · noneconsensus · none
52
citations
affno abstractunlabeled
Unrestricted Nogood Recording in CSP Search
George Katsirelos, Fahiem Bacchus
2003· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
47
citations

How this was built: Screen · Findings · About