{"id":"W4285287188","doi":"10.2139/ssrn.4136029","title":"2-Stage Swarm Search Feature Selection for Classification of High Dimension Bioinformatics Dataset","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Feature selection; Selection (genetic algorithm); Stage (stratigraphy); Artificial intelligence; Pattern recognition (psychology); Computer science; Swarm behaviour; Feature (linguistics); Data mining; Machine learning; Computational biology; Biology","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":[0.001046943,0.0009873718,0.001538236,0.001158038,0.0006374512,0.0006843122,0.00114197,0.001132222,0.003527987],"category_scores_gemma":[0.001844993,0.0002577045,0.001347971,0.001196297,0.0002202102,0.0005273698,0.0006466213,0.0006592052,0.0008388886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003488421,"about_ca_system_score_gemma":0.001460205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007539042,"about_ca_topic_score_gemma":0.01080749,"domain_scores_codex":[0.9995408,0.00007979952,0.00005082216,0.0001126142,0.0001027482,0.000113224],"domain_scores_gemma":[0.9995104,0.0001792846,0.00002566384,0.00006147746,0.0001874734,0.00003575591],"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":[0.001903779,0.001047276,0.01450346,0.0002823565,0.0003771015,0.0002851019,0.0001906943,0.1578375,0.01942096,0.001237605,0.02024873,0.7826654],"study_design_scores_gemma":[0.000104718,0.0002703567,0.004065085,0.0000120121,0.00005056126,0.000055444,0.00005284593,0.9899491,0.003751795,0.0005170586,0.001155786,0.00001528054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4410549,0.001330548,0.5444483,0.0005631793,0.0004403455,0.0005839553,0.002595784,0.005272856,0.003710154],"genre_scores_gemma":[0.7637556,0.000209479,0.2207801,0.0002326859,0.0001271575,0.0007262464,0.006449164,0.0001478912,0.007571693],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007539042,"threshold_uncertainty_score":0.01499033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009869589778197062,"score_gpt":0.2760159001053437,"score_spread":0.2661463103271466,"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."}}