{"id":"W1537340563","doi":"10.1007/3-540-47887-6_12","title":"Toward Bayesian Classifiers with Accurate Probabilities","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Naive Bayes classifier; Ranking (information retrieval); Artificial intelligence; Receiver operating characteristic; Machine learning; Bayesian probability; Bayes' theorem; Decision tree; Data mining; Pattern recognition (psychology); Statistics; Support vector machine; Mathematics","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006133805,0.0007592648,0.000659729,0.0006787262,0.0002886324,0.001058045,0.003888627,0.0004085709,0.00005163791],"category_scores_gemma":[0.00005600297,0.0006060055,0.0001300023,0.00069213,0.001265455,0.0009497032,0.0008404268,0.001182872,0.00006555446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003417414,"about_ca_system_score_gemma":0.0007577463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000234842,"about_ca_topic_score_gemma":0.00004205728,"domain_scores_codex":[0.9951481,0.00004651682,0.0005779286,0.002042861,0.001205208,0.0009794466],"domain_scores_gemma":[0.9970261,0.0003025893,0.0003022829,0.001709049,0.0003486427,0.0003112693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001738077,0.00006351087,0.000061005,0.0001552401,0.00003563921,0.0003156192,0.003312318,0.06291985,0.00003009716,0.179192,0.000101762,0.7537956],"study_design_scores_gemma":[0.000239733,0.0003598167,0.00002230936,0.0005777769,0.00001032648,0.0001539938,5.073011e-7,0.7431865,0.0002672561,0.2534368,0.0007869725,0.0009579888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000274329,0.0002811958,0.9832898,0.001751203,0.000811001,0.000400584,0.000004840712,0.0003423333,0.01309159],"genre_scores_gemma":[0.4046592,0.00009162468,0.5913753,0.001720902,0.0003813677,0.0000276863,0.000004013055,0.00006459389,0.001675301],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7528376,"threshold_uncertainty_score":0.999979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04311010230782662,"score_gpt":0.242856787131332,"score_spread":0.1997466848235054,"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."}}