{"id":"W4390906038","doi":"10.1109/transai60598.2023.00048","title":"Feature Selection via Independent Domination","year":2023,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Feature selection; Selection (genetic algorithm); Computer science; Feature (linguistics); Artificial intelligence; Pattern recognition (psychology)","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":[0.0002747149,0.00004697992,0.00003800702,0.0001300037,0.00009716176,0.00009922131,0.0002284423,0.00004484706,0.0000190957],"category_scores_gemma":[0.0000377,0.00004023633,0.00001640388,0.0007035457,0.000004316486,0.0003199728,0.0000672144,0.0001057439,0.0007205542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002446669,"about_ca_system_score_gemma":0.00001462141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002387276,"about_ca_topic_score_gemma":0.00002235085,"domain_scores_codex":[0.9994276,0.00004223032,0.00005161773,0.0001992429,0.0001766429,0.0001026745],"domain_scores_gemma":[0.9996786,0.00002920312,0.00003375551,0.0001895789,0.00003965907,0.00002921411],"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":[0.000004511528,0.0000346064,0.006600703,0.00001248773,0.000009548227,0.000003406248,0.0003436063,0.0005627509,0.01585293,0.1649008,0.08419105,0.7274836],"study_design_scores_gemma":[0.000142731,0.00002780151,0.175016,0.00000240893,0.00000157166,0.00001108123,0.00001247248,0.7677644,0.001674881,0.001902224,0.05335435,0.00009003769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004809796,0.000004652406,0.9769447,0.01063337,0.0002162091,0.00006362011,3.449728e-7,0.0008808054,0.006446493],"genre_scores_gemma":[0.9717739,0.000007043,0.01307606,0.0001642472,0.0000682649,0.00001227833,0.00005155229,0.000004291157,0.01484238],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9669641,"threshold_uncertainty_score":0.9261507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01107445145980477,"score_gpt":0.2612648775403473,"score_spread":0.2501904260805425,"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."}}