{"id":"W2135420268","doi":"10.1109/grc.2007.40","title":"Naïve Bayes Text Classifier","year":2007,"lang":"en","type":"article","venue":"2007 IEEE International Conference on Granular Computing (GRC 2007)","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University","funders":"","keywords":"Naive Bayes classifier; Computer science; Bayes' theorem; Support vector machine; Artificial intelligence; Machine learning; Detector; Classifier (UML); Bayesian probability; Information retrieval; Data mining","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001325139,0.0004319678,0.0003389218,0.0006879121,0.0003219351,0.0006082693,0.002751708,0.0002769299,0.0006369083],"category_scores_gemma":[0.0002309544,0.000418536,0.00019955,0.000538956,0.0002415108,0.0005357633,0.0003288498,0.0006263896,0.002019621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002422164,"about_ca_system_score_gemma":0.0001315882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003160731,"about_ca_topic_score_gemma":0.00001691479,"domain_scores_codex":[0.9962035,0.00008026652,0.0008558437,0.0009529921,0.001161585,0.0007458274],"domain_scores_gemma":[0.9974197,0.0003340518,0.0004587866,0.0009820425,0.0006064997,0.0001989207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006561218,0.0003633664,0.003795926,0.00001606645,0.00009815882,0.00006853428,0.0004676294,0.0001837841,0.006740526,0.7801839,0.03503496,0.1729816],"study_design_scores_gemma":[0.004017391,0.0006914929,0.03033517,0.0007216603,0.00005294131,0.0002600985,0.000932888,0.2473689,0.03607211,0.08312909,0.5928733,0.003544944],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02107755,0.00007610444,0.8960201,0.002423766,0.005307004,0.0002562521,0.000009928619,0.0009023241,0.07392693],"genre_scores_gemma":[0.9498128,0.00004760843,0.04350821,0.001220557,0.0005639984,0.000008724181,0.00002831158,0.0000293757,0.004780462],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9287352,"threshold_uncertainty_score":0.9998267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07050096873332103,"score_gpt":0.3294173998244482,"score_spread":0.2589164310911272,"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."}}