{"id":"W4389545043","doi":"10.1109/icit59216.2023.10335879","title":"Prediction of Polycystic Ovary Syndrome Using Genetic Algorithm-driven Feature Selection","year":2023,"lang":"en","type":"article","venue":"","topic":"Ovarian function and disorders","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Polycystic ovary; Logistic regression; Infertility; Miscarriage; Feature selection; Computer science; Feature (linguistics); Artificial intelligence; Algorithm; Gynecology; Machine learning; Medicine; Biology; Pregnancy; Endocrinology; Diabetes mellitus; Genetics; Insulin resistance","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005832094,0.00009020584,0.0001563421,0.0002767687,0.00005580871,0.000006373416,0.00002530986,0.0001117658,0.0003760379],"category_scores_gemma":[0.00003007865,0.00008131961,0.00006630393,0.0008192348,0.00002779027,0.00005180419,0.00001527211,0.000112191,0.0000723392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004606594,"about_ca_system_score_gemma":0.00008417219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006415744,"about_ca_topic_score_gemma":0.000001565907,"domain_scores_codex":[0.9992857,0.0000215067,0.0001577074,0.0001748654,0.0002049911,0.0001552186],"domain_scores_gemma":[0.9996721,0.00001677485,0.00004563684,0.0001192671,0.00006771197,0.00007851976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002111691,0.001685901,0.3869654,0.001608866,0.002304506,0.0007710294,0.00140929,0.02885689,0.2848827,0.0005963424,0.1685327,0.1202747],"study_design_scores_gemma":[0.001488424,0.0004631333,0.6574072,0.00006519794,0.0002028646,0.0009508881,0.0002587589,0.3373293,0.000544313,0.00008885742,0.001107072,0.00009408742],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8495677,0.0001648518,0.1412168,0.0009208934,0.001302624,0.0007130501,0.00003276564,0.0009248898,0.005156469],"genre_scores_gemma":[0.9630098,0.00003614331,0.02813061,0.000256337,0.000153575,0.000008805046,0.00008884114,0.00003318633,0.008282648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3084724,"threshold_uncertainty_score":0.4117352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02300807277988216,"score_gpt":0.2516702038744195,"score_spread":0.2286621310945373,"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."}}