{"id":"W7129519456","doi":"10.1109/icecmsn68058.2025.11383242","title":"A GeneSwarm-Enhanced Hybrid Ensemble Model for Predicting Cardiac Outcomes in Kawasaki Disease","year":2025,"lang":"","type":"article","venue":"","topic":"Kawasaki Disease and Coronary Complications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Kawasaki disease; Feature (linguistics); Ensemble learning; Ensemble forecasting; Support vector machine; Hyperparameter; Outlier; Particle swarm optimization","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":[0.0007703207,0.0005852124,0.0009239229,0.0006124735,0.0002679407,0.0005918187,0.0006537262,0.0005678088,0.000565363],"category_scores_gemma":[0.001136179,0.0002208292,0.0007299418,0.0004176092,0.0001366599,0.0003718534,0.0004293026,0.0006509654,0.0001572982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003887804,"about_ca_system_score_gemma":0.0004940568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009674025,"about_ca_topic_score_gemma":0.007230015,"domain_scores_codex":[0.9997899,0.00006821017,0.00001414878,0.00005349907,0.00003499442,0.00003918789],"domain_scores_gemma":[0.9997248,0.0001263537,0.00002915761,0.00001769607,0.00008427691,0.00001764572],"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":[0.0002152945,0.0001192584,0.0172896,0.000025685,0.0002075435,0.0001714161,0.00005864141,0.879171,0.001778113,0.0006037098,0.001699434,0.09866025],"study_design_scores_gemma":[0.000002849763,0.00002209343,0.0009253735,0.000002818175,0.00001786543,0.00001051372,0.000003861625,0.9985837,0.0001235455,0.0002102551,0.00009371542,0.000003471867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6074516,0.002177919,0.3854735,0.0007733625,0.0001882884,0.00006081795,0.0007000894,0.000850874,0.002323552],"genre_scores_gemma":[0.9825717,0.0002728858,0.01512161,0.00008815488,0.00005658907,0.00005067182,0.0005026088,0.00001509241,0.001320606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009674025,"threshold_uncertainty_score":0.01923543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02307849403193502,"score_gpt":0.3155758565376725,"score_spread":0.2924973625057375,"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."}}