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Record W2041308874 · doi:10.1109/ictai.2012.19

SAT with Global Constraints

2012· article· en· W2041308874 on OpenAlexaff
Shahariar Chowdhury, Jia-Huai You

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicConstraint Satisfaction and Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSolverUsabilityComputer scienceConstraint satisfaction problemBoolean satisfiability problemRepresentation (politics)Constraint (computer-aided design)Theoretical computer scienceConstraint satisfactionConstraint programmingProblem solverProgramming languageMathematical optimizationComputational scienceHuman–computer interactionArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

We present a tight integration of SAT with CP, called SAT(gc), which embeds global constraints into SAT. A prototype is implemented by integrating the state of the art SAT solver ZCHAFF and the generic constraint solver GECODE. Experiments are carried out for benchmarks from puzzle domains and planning domains to reveal insights in compact representation, solving effectiveness, and novel usability of the new framework.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.004
Science and technology studies0.0010.002
Scholarly communication0.0030.005
Open science0.0040.006
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0150.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.227
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2012
Admission routes1
Has abstractyes

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