{"id":"W139033644","doi":"","title":"On Reasoning with Default Rules and Exceptions","year":2001,"lang":"en","type":"article","venue":"","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Default rule; Default logic; Property (philosophy); Default; sort; Computer science; Similarity (geometry); Relation (database); Artificial intelligence; Natural language processing; Information retrieval; Data mining; Economics; Epistemology","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":[0.00005555712,0.0000573274,0.00004756765,0.00003125078,0.0000924278,0.0001066199,0.0001392473,0.00002024825,0.00001823803],"category_scores_gemma":[0.000008176065,0.0000399273,0.000007686708,0.0000934687,0.0000227394,0.0001528765,0.00003482377,0.00005889189,0.00005348982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005548034,"about_ca_system_score_gemma":0.00001480725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004062216,"about_ca_topic_score_gemma":0.00001672211,"domain_scores_codex":[0.9995617,0.00001142164,0.00004881969,0.0001755955,0.00008708204,0.0001153865],"domain_scores_gemma":[0.9996904,0.00003043933,0.00001294263,0.0001825626,0.00002577207,0.00005789032],"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":[0.000004817914,0.0000254953,0.001380272,0.000001437563,0.000004220431,0.00001370208,0.0001968408,0.0003189594,0.00007855857,0.9344334,0.0004090758,0.06313323],"study_design_scores_gemma":[0.0007420059,0.0006886504,0.04419232,0.0002201039,0.00001168034,0.000478807,0.0001153178,0.7971152,0.0003740867,0.1526452,0.002731575,0.0006850361],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2033361,0.00001798201,0.7736017,0.0004733494,0.00001505125,0.00001889205,1.534851e-7,0.0001129938,0.02242374],"genre_scores_gemma":[0.8974651,0.00002013631,0.101256,0.0003673956,0.0000122771,0.000003331575,3.762835e-7,0.000002620092,0.0008728054],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7967963,"threshold_uncertainty_score":0.1628188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686600645700802,"score_gpt":0.2428413817756172,"score_spread":0.2259753753186092,"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."}}