{"id":"W2142185590","doi":"10.1007/11427834_10","title":"Rough Sets and Bayes Factor","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":120,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rough set; Computer science; Bayes' theorem; Bayesian probability; Data mining; Dominance-based rough set approach; Naive Bayes classifier; Set (abstract data type); Bayes factor; Artificial intelligence; Inverse; Factor (programming language); Machine learning; Algorithm; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008276958,0.001171843,0.002611131,0.003956544,0.0009015481,0.004460883,0.001220138,0.002030834,0.005546818],"category_scores_gemma":[0.03240821,0.0007167557,0.001023995,0.003321771,0.003387712,0.00676544,0.001079247,0.00273995,0.001095374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001691128,"about_ca_system_score_gemma":0.001134977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001629794,"about_ca_topic_score_gemma":0.0009121708,"domain_scores_codex":[0.9949478,0.002650572,0.0002529853,0.0005448856,0.001452055,0.0001516378],"domain_scores_gemma":[0.9864181,0.01122139,0.0005762395,0.0008396442,0.0008211269,0.0001235783],"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":[0.000016339,0.00001191026,0.0002172599,0.0001454273,0.00006049936,0.00005287467,0.0001573595,0.005041464,0.00005381566,0.9476876,0.003871354,0.04268424],"study_design_scores_gemma":[0.000002730623,0.000004346739,0.00009836321,0.00003392453,0.00001224974,0.0000432559,0.00002469227,0.00473959,0.00003021748,0.9923307,0.002670788,0.000008983029],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01328626,0.06686726,0.8387641,0.00950227,0.002248607,0.0001026831,0.0004097174,0.0002720421,0.06854706],"genre_scores_gemma":[0.5988327,0.0588337,0.3048114,0.001973934,0.006910714,0.0004104093,0.0004725269,0.0001455541,0.02760908],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008276958,"threshold_uncertainty_score":0.04377323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02013149832196776,"score_gpt":0.2444761760074638,"score_spread":0.224344677685496,"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."}}