{"id":"W4407956228","doi":"10.18280/isi.300212","title":"Optimizing Feature Selection Based on the Black-Winged Kite Algorithm","year":2025,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Kite; Selection (genetic algorithm); Feature selection; Computer science; Algorithm; Feature (linguistics); Artificial intelligence; 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":[0.0001532367,0.0001621997,0.0001177274,0.0001831986,0.000356116,0.0001688129,0.0001377751,0.00009794126,0.00001899404],"category_scores_gemma":[0.00005122081,0.0001300089,0.00005630302,0.0006667775,0.00005806283,0.0007093257,0.00001535457,0.0002452322,0.00005106028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002614015,"about_ca_system_score_gemma":0.00003010315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005765578,"about_ca_topic_score_gemma":0.000002456984,"domain_scores_codex":[0.9993002,0.00001789369,0.0002461588,0.00008640226,0.0001382098,0.0002111816],"domain_scores_gemma":[0.999505,0.00009167266,0.00006230274,0.0001984742,0.0001101513,0.00003241119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006922507,0.00001174578,0.00002361631,0.0001266731,0.0000359905,2.442135e-7,0.0009474962,0.7160664,0.0002970475,0.005246821,0.004408828,0.2728282],"study_design_scores_gemma":[0.0001866075,0.00001576699,0.0004942901,0.0001305635,0.00001251959,0.000001379258,0.0003522778,0.9658131,0.003488746,0.001405842,0.02795636,0.0001425757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002956728,0.00004756161,0.9714237,0.0003072848,0.0002212716,0.0003941263,0.00002178282,0.0005366879,0.02409079],"genre_scores_gemma":[0.929347,0.00003961674,0.06886717,0.0008669157,0.0001280052,0.0002976221,0.0001353792,0.00002676947,0.0002914675],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9263903,"threshold_uncertainty_score":0.5301609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006307421788952142,"score_gpt":0.2125233838199577,"score_spread":0.2062159620310056,"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."}}