{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000747506,0.0007312187,0.0007927329,0.001275114,0.000222809,0.0004859137,0.000525991,0.0005932378,0.000524172],"category_scores_gemma":[0.00224296,0.0001458236,0.0008062169,0.0007526449,0.000143714,0.0002315252,0.0002703219,0.0005550256,0.0001776755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003534172,"about_ca_system_score_gemma":0.00068947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006344468,"about_ca_topic_score_gemma":0.004471472,"domain_scores_codex":[0.9996642,0.00009554302,0.00003343656,0.00009384206,0.00005606174,0.00005690126],"domain_scores_gemma":[0.9992366,0.0004586556,0.00007624194,0.00002866029,0.0001577752,0.00004208802],"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":[0.0009580766,0.000991103,0.2276975,0.0001079801,0.0005142196,0.001013907,0.00006580316,0.375202,0.01277186,0.0004247024,0.005395676,0.3748572],"study_design_scores_gemma":[0.00003494224,0.0001045794,0.01511956,0.000007460926,0.00004014618,0.0001614939,0.00001492456,0.9828153,0.001188453,0.000267452,0.0002343066,0.00001134136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8203049,0.001248829,0.1735471,0.0008515279,0.0001319155,0.0001718984,0.001328301,0.001533296,0.0008822547],"genre_scores_gemma":[0.9719248,0.0001361602,0.02563622,0.0001075462,0.00003745402,0.0000649196,0.001654824,0.0000171623,0.0004208958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006344468,"threshold_uncertainty_score":0.01261508,"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."}}