{"id":"W4388206534","doi":"10.1109/ccece58730.2023.10288649","title":"Classification of Parkinson Disease with Feature Selection using Genetic Algorithm","year":2023,"lang":"en","type":"article","venue":"","topic":"Parkinson's Disease Mechanisms and Treatments","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Feature selection; Computer science; Selection (genetic algorithm); Parkinson's disease; Genetic algorithm; Artificial intelligence; Statistical classification; Disease; Pattern recognition (psychology); Feature (linguistics); Algorithm; Machine learning; Medicine; Internal medicine","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":[0.001067501,0.0006489018,0.0008675522,0.001758774,0.0003634242,0.0006409043,0.0005504474,0.0006198617,0.0005399318],"category_scores_gemma":[0.002556278,0.0002532756,0.0008530871,0.001080671,0.0002580005,0.0003267048,0.0002953548,0.0003757981,0.0001323907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007040345,"about_ca_system_score_gemma":0.0009399793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007996149,"about_ca_topic_score_gemma":0.004349899,"domain_scores_codex":[0.9995713,0.0001427472,0.00003434401,0.00009508521,0.00009722698,0.00005929032],"domain_scores_gemma":[0.9991178,0.0005048221,0.00007288045,0.00003291172,0.0002496292,0.00002195825],"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":[0.0003130008,0.0002856335,0.01496627,0.00007854166,0.0001950153,0.0002404516,0.0001119475,0.6445965,0.01052686,0.001329513,0.001362609,0.3259938],"study_design_scores_gemma":[0.00001720932,0.00006332431,0.001780538,0.000006299318,0.0000252045,0.00004289532,0.00001763534,0.9958438,0.001481906,0.0005152596,0.000197616,0.000008336291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4360642,0.0006167914,0.5593702,0.0003625643,0.00007180645,0.0002518822,0.00029767,0.001187348,0.001777573],"genre_scores_gemma":[0.8061572,0.0001324589,0.1922373,0.00006428912,0.00001904167,0.0001937603,0.0004536491,0.00003512528,0.0007071025],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007996149,"threshold_uncertainty_score":0.01589918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02640230056729545,"score_gpt":0.2819345914427026,"score_spread":0.2555322908754072,"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."}}