{"id":"W2736770525","doi":"","title":"Merging the Local and Global Approaches to Probabilistic Satisfiability","year":2004,"lang":"en","type":"article","venue":"Les Cahiers du GERAD","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Probabilistic logic; Satisfiability; Consistency (knowledge bases); Mathematics; Logical consequence; Set (abstract data type); Mathematical optimization; Computer science; Algorithm; Discrete mathematics; Artificial intelligence; Statistics","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":[0.0004094251,0.0001593815,0.0001584829,0.00002263653,0.0003886855,0.0001779454,0.0005617373,0.0000823689,0.000002524642],"category_scores_gemma":[0.0001797794,0.0001062165,0.00005362501,0.000351728,0.0004421561,0.0001549734,0.0002168451,0.000164971,0.0000211958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002731626,"about_ca_system_score_gemma":0.00008453312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001538672,"about_ca_topic_score_gemma":0.0001613555,"domain_scores_codex":[0.9987907,0.00009238091,0.00015726,0.000457031,0.0001865055,0.0003161189],"domain_scores_gemma":[0.9992104,0.000106505,0.00004003999,0.0004586229,0.0000314361,0.000153021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004707028,0.00003558288,0.003162357,0.0000182625,0.00001015894,0.000006989645,0.00444133,0.0007903178,0.000006696732,0.9488727,0.00007188055,0.042579],"study_design_scores_gemma":[0.000821392,0.0002122503,0.0859929,0.00003099662,0.00002810424,0.0001602708,0.0007210305,0.01401671,0.000217412,0.8927609,0.004477838,0.0005601977],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3037465,0.0003073936,0.6860078,0.004486554,0.0001877539,0.0002818883,0.000001911452,0.0001288946,0.004851262],"genre_scores_gemma":[0.9672194,0.000004715689,0.03227317,0.0003530961,0.00007199348,0.00002887953,6.928384e-7,0.0000050015,0.00004305154],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6634729,"threshold_uncertainty_score":0.4331383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02820314155902571,"score_gpt":0.210460745074942,"score_spread":0.1822576035159163,"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."}}