{"id":"W2966464227","doi":"10.48550/arxiv.1908.00089","title":"A Model of Random Industrial SAT","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Azrieli Foundation","keywords":"Satisfiability; Disjoint sets; Generalization; Set (abstract data type); Focus (optics); Boolean satisfiability problem; Mathematics; Computer science; Discrete mathematics; Algorithm; Combinatorics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001615259,0.0001652194,0.0002840573,0.0002285435,0.00004198189,0.00004378189,0.0007427061,0.0002900551,0.00004215183],"category_scores_gemma":[0.00003160356,0.000192864,0.0001740939,0.0002868532,0.00006163259,0.0002493335,0.0007705751,0.0003619552,0.00003714549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009091044,"about_ca_system_score_gemma":0.0003950506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004229971,"about_ca_topic_score_gemma":0.00001493075,"domain_scores_codex":[0.998973,0.00007998312,0.0001845086,0.0005337952,0.00007995508,0.0001487404],"domain_scores_gemma":[0.9987475,0.00007185313,0.0002659509,0.0007158873,0.0001257255,0.00007313779],"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":[0.00004267046,0.00002129431,0.002070394,0.00001621501,0.00003311842,0.000005327655,0.00009414656,0.9500936,0.00002728798,0.04643294,0.0001459853,0.001016994],"study_design_scores_gemma":[0.001578635,0.00001556211,0.0001413801,0.00004187041,0.00003107658,8.848318e-7,0.0000153349,0.9896955,0.00007217006,0.008182764,0.00003997811,0.0001848111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09337823,0.000006911435,0.9023733,0.00006009572,0.0005748907,0.0002687971,0.00001774631,0.00009362611,0.003226439],"genre_scores_gemma":[0.9956999,0.00005137961,0.002980304,0.0000353841,0.00002818682,2.866194e-7,0.00001271149,0.000006921207,0.001184917],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9023217,"threshold_uncertainty_score":0.7864764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1335920945488172,"score_gpt":0.1843312370561455,"score_spread":0.05073914250732836,"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."}}