{"id":"W4367727818","doi":"10.1109/access.2023.3272556","title":"Bio-Inspired Feature Selection Algorithms With Their Applications: A Systematic Literature Review","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Feature selection; Machine learning; Artificial intelligence; Metaheuristic; Particle swarm optimization; Algorithm; Support vector machine; Feature (linguistics); Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004523754,0.0001639897,0.0002447733,0.00017948,0.0002028152,0.0006319577,0.001168407,0.00007409554,0.000001904568],"category_scores_gemma":[0.00004682025,0.0001061455,0.00004562368,0.003638933,0.00001638474,0.0009019835,0.00008190706,0.0002382865,0.00009309178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003148162,"about_ca_system_score_gemma":0.0000460005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006253643,"about_ca_topic_score_gemma":0.000007359962,"domain_scores_codex":[0.9987184,0.0001605328,0.0002080235,0.0004553645,0.0002618606,0.0001957881],"domain_scores_gemma":[0.9986568,0.00009314792,0.0002123245,0.0007916378,0.0001822525,0.00006384514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003411819,0.0004770658,0.006260565,0.451018,0.000502962,0.0001021179,0.002832876,0.001083833,0.00246924,0.02726277,0.2061544,0.3018021],"study_design_scores_gemma":[0.001796193,0.0004741732,0.0228185,0.225122,0.0003720628,0.001081683,0.0001136076,0.6153697,0.003134197,0.002943241,0.124051,0.002723605],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001708968,0.02395726,0.9644471,0.007023348,0.0002423836,0.002000462,0.00002133172,0.001658222,0.0004789425],"genre_scores_gemma":[0.6744182,0.1455125,0.09857942,0.02396381,0.004065981,0.02900204,0.004285989,0.0004611971,0.01971087],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8658677,"threshold_uncertainty_score":0.6093982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02326287812927302,"score_gpt":0.3053787232636258,"score_spread":0.2821158451343528,"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."}}