{"id":"W4391307056","doi":"10.1109/smc53992.2023.10394281","title":"Feature Selection Using Evolutionary Techniques","year":2023,"lang":"en","type":"article","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Feature selection; Selection (genetic algorithm); Artificial intelligence; Feature (linguistics); Pattern recognition (psychology); Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001367709,0.001101188,0.001473356,0.002317204,0.0006946328,0.000886763,0.0009774361,0.0008555016,0.001615616],"category_scores_gemma":[0.003551341,0.0004527529,0.001247772,0.002061144,0.0003734334,0.0007298291,0.0007765323,0.0005763107,0.0004303821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004324864,"about_ca_system_score_gemma":0.0005667412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001574381,"about_ca_topic_score_gemma":0.001267459,"domain_scores_codex":[0.9992121,0.0001965822,0.00005642732,0.0001664595,0.0002849747,0.00008339903],"domain_scores_gemma":[0.9990302,0.0004464989,0.00008228226,0.00007039385,0.0003368149,0.00003384299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000114291,0.0001669684,0.003840248,0.0001861293,0.0002109432,0.0003256773,0.0001663152,0.3882363,0.02096775,0.007488048,0.002550657,0.5757467],"study_design_scores_gemma":[0.00003339141,0.00007467457,0.001098557,0.00001742146,0.00004660278,0.0001573666,0.00003695052,0.9879745,0.003898246,0.003981706,0.002662899,0.0000176363],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03065348,0.000407375,0.966116,0.0001585792,0.00006538793,0.0001370517,0.00005956478,0.0004229816,0.001979591],"genre_scores_gemma":[0.3650494,0.0003672358,0.631112,0.0001895306,0.00007837449,0.0004452485,0.0003324483,0.0001386843,0.002287013],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002317204,"threshold_uncertainty_score":0.007233202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01965297109221247,"score_gpt":0.2791299483197043,"score_spread":0.2594769772274919,"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."}}