{"id":"W1871585472","doi":"10.14288/1.0051500","title":"SATenstein : automatically building local search SAT solvers from components","year":2009,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":116,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Boolean satisfiability problem; Satisfiability; Task (project management); Context (archaeology); Solver; Local search (optimization); Range (aeronautics); Satisfiability modulo theories; Theoretical computer science; Selection (genetic algorithm); Programming language; Algorithm; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002351001,0.001427588,0.000887607,0.001065524,0.0006352019,0.001903117,0.003594709,0.001251986,0.008954324],"category_scores_gemma":[0.01036287,0.001242179,0.001581859,0.001443975,0.001256823,0.003392539,0.003095456,0.002119204,0.002583949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001399536,"about_ca_system_score_gemma":0.002628358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002167957,"about_ca_topic_score_gemma":0.004884949,"domain_scores_codex":[0.9980121,0.0007047055,0.0001530013,0.0003873201,0.0005877692,0.0001551085],"domain_scores_gemma":[0.9961419,0.002119367,0.000228327,0.00106279,0.0003541967,0.00009339786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004152933,0.0003226219,0.004113709,0.001072351,0.0003167574,0.0002678215,0.0004484276,0.4584784,0.02023801,0.08478189,0.02026928,0.4092755],"study_design_scores_gemma":[0.00007804243,0.00005167748,0.0001985008,0.00002564589,0.00003583293,0.00006643619,0.00004704862,0.9667627,0.01009472,0.01485867,0.007765378,0.00001527886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01261048,0.0001199117,0.9653468,0.0001165143,0.00003174293,0.0002533811,0.0002269797,0.01762592,0.003668324],"genre_scores_gemma":[0.1138269,0.0001070189,0.8809207,0.0001198791,0.0000185931,0.0004562613,0.001101888,0.001616297,0.00183248],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008954324,"threshold_uncertainty_score":0.02995515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009889219578066074,"score_gpt":0.1833860784666706,"score_spread":0.1734968588886046,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}