{"id":"W2151103537","doi":"10.5430/air.v2n2p77","title":"An adaptive methodology to discretize and select features","year":2013,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministerio de Economía y Competitividad","keywords":"Computer science; Feature (linguistics); Discretization; Artificial intelligence; Machine learning; Data mining; Feature selection; Pattern recognition (psychology); Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001218536,0.00009821147,0.0001264173,0.000163962,0.0003563633,0.0004281434,0.00090857,0.00006273568,0.0000524049],"category_scores_gemma":[0.0001726427,0.0000801198,0.00002345807,0.001082371,0.0001898831,0.000386725,0.0003357574,0.0003508212,0.000453551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002211224,"about_ca_system_score_gemma":0.00004434287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001038568,"about_ca_topic_score_gemma":0.0002747811,"domain_scores_codex":[0.9978885,0.0005432991,0.0001805022,0.0005361746,0.0003096151,0.0005418976],"domain_scores_gemma":[0.9979566,0.0008812607,0.00002061309,0.0005086978,0.0003205742,0.0003122131],"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":[0.000008013263,0.00003180451,0.00001783695,0.000001110747,0.000003145427,0.000001735092,0.0005182942,0.0001641052,0.02321904,0.543404,0.0008302489,0.4318006],"study_design_scores_gemma":[0.000008966251,0.0007382011,0.00149015,0.000009851685,0.000001465504,0.00001322824,0.000783545,0.09818649,0.1059264,0.791776,0.0008687899,0.0001969456],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0574063,0.00008903405,0.9304203,0.01073445,0.00006358267,0.0005920545,0.000001169573,0.00007802178,0.0006151115],"genre_scores_gemma":[0.907644,0.00003166597,0.09156808,0.0002607186,0.0001355493,0.0001903616,8.566666e-7,0.00000759811,0.0001612004],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8502377,"threshold_uncertainty_score":0.5829631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.335412719620955,"score_gpt":0.4778933484378903,"score_spread":0.1424806288169352,"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."}}