{"id":"W4414824476","doi":"10.1016/j.euroneuro.2025.08.197","title":"M1. EVALUATING MACHINE LEARNING MODELS FOR PREDICTION OF ATTENTION DEFICIT HYPERACTIVITY DISORDER AMONG AUTISTIC INDIVIDUALS USING GENETIC DATA","year":2025,"lang":"en","type":"article","venue":"European Neuropsychopharmacology","topic":"Attention Deficit Hyperactivity Disorder","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Attention deficit hyperactivity disorder; Autism; Random forest; Logistic regression; Hyperparameter; Autism spectrum disorder; Cognition; Hyperparameter optimization; Gradient boosting","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":[0.009232135,0.002208994,0.0008576342,0.001530711,0.0007458264,0.001400574,0.001554008,0.002479413,0.008236468],"category_scores_gemma":[0.02091459,0.000582254,0.001759727,0.0007963861,0.000385383,0.001094191,0.001305643,0.00150425,0.002494362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001194787,"about_ca_system_score_gemma":0.001643632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01614943,"about_ca_topic_score_gemma":0.01597157,"domain_scores_codex":[0.997862,0.001154513,0.0001633813,0.0004430655,0.0002252075,0.0001518574],"domain_scores_gemma":[0.9895917,0.008508067,0.0002583951,0.000561722,0.0007922706,0.0002879514],"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":[0.01156221,0.00231612,0.1784044,0.001322505,0.004937502,0.0006038708,0.0002163186,0.429362,0.004367277,0.002416089,0.0843019,0.2801898],"study_design_scores_gemma":[0.00108757,0.002058913,0.02623073,0.0001206939,0.0005227721,0.000172655,0.0001721086,0.9611241,0.003963741,0.001871025,0.002628088,0.00004764942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.896973,0.003102844,0.04207822,0.00374099,0.0008350905,0.0007758897,0.03516832,0.008878216,0.008447389],"genre_scores_gemma":[0.8965203,0.0004083506,0.0552539,0.0004845257,0.0002088392,0.0004446817,0.04142391,0.0003091993,0.004946345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01614943,"threshold_uncertainty_score":0.04882479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1148522212851231,"score_gpt":0.3900794530273603,"score_spread":0.2752272317422372,"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."}}