{"id":"W3035389942","doi":"","title":"Online Bayesian Moment Matching based SAT Solver Heuristics","year":2020,"lang":"en","type":"article","venue":"International Conference on Machine Learning","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Heuristics; Computer science; Matching (statistics); Solver; Bayesian probability; Moment (physics); Algorithm; Artificial intelligence; Mathematics; Statistics; Programming language; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001947987,0.0001990595,0.0001986535,0.00007664971,0.0001482836,0.000354957,0.0009810022,0.00005290034,0.00027123],"category_scores_gemma":[0.0001158868,0.0001872119,0.00008065841,0.0001636475,0.00002197266,0.0002250266,0.0001766647,0.0006320002,0.0001599885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006316257,"about_ca_system_score_gemma":0.00007604018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008479983,"about_ca_topic_score_gemma":0.00001323845,"domain_scores_codex":[0.9982869,0.0001223106,0.0003260668,0.0004530884,0.0005814493,0.000230183],"domain_scores_gemma":[0.999199,0.00008115226,0.0001785055,0.0002040977,0.0001711683,0.000166057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001681401,0.0006527342,0.0100565,0.0001053984,0.0001843747,0.0003698648,0.002827429,0.2052046,0.005150482,0.668062,0.002042161,0.1051762],"study_design_scores_gemma":[0.000463553,0.0001221398,0.0009941634,0.00008060345,0.000002971484,0.000004265537,0.00005126459,0.9685887,0.00006563722,0.0007229689,0.02869996,0.0002037488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005139179,0.00002430652,0.964314,0.023081,0.0004528332,0.00009571218,0.00007542445,0.0002327755,0.006584712],"genre_scores_gemma":[0.9806139,0.000007081333,0.01534821,0.003180315,0.0002039301,0.000006762962,0.0002042887,0.00001399032,0.0004214912],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9754748,"threshold_uncertainty_score":0.7634279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04184371776120862,"score_gpt":0.2904388463723157,"score_spread":0.248595128611107,"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."}}