{"id":"W4323041974","doi":"10.18280/mmep.100110","title":"Ensemble Machine Learning Based Identification of Adult Epilepsy","year":2023,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Epilepsy; Identification (biology); Ensemble learning; Machine learning; Artificial intelligence; Computer science; Psychology; Neuroscience; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007552775,0.000473168,0.0006385448,0.001135021,0.0001944861,0.0003403428,0.000336331,0.0004058002,0.0005136157],"category_scores_gemma":[0.001789546,0.0001126539,0.0004695247,0.00063212,0.0000983252,0.0004748156,0.0003722278,0.0003658213,0.0002132162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002074453,"about_ca_system_score_gemma":0.0002307184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002490257,"about_ca_topic_score_gemma":0.002951782,"domain_scores_codex":[0.9996753,0.00006915927,0.00002658241,0.00009222489,0.00007907206,0.0000576213],"domain_scores_gemma":[0.99944,0.0002046072,0.00007249552,0.00006289613,0.0001924194,0.00002760359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002855028,0.00021438,0.06734516,0.00008819885,0.0003029144,0.0005037641,0.0001170787,0.2388055,0.02263751,0.001336496,0.004096359,0.6642671],"study_design_scores_gemma":[0.000003007499,0.00005578088,0.01203983,0.000006431459,0.0000317785,0.0001457212,0.0000206039,0.9834843,0.003014625,0.0006538312,0.0005335588,0.00001050768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5520903,0.001524517,0.4408749,0.0003695966,0.0001423058,0.00005480567,0.0006406772,0.001260796,0.003042093],"genre_scores_gemma":[0.9720567,0.0002645717,0.02615856,0.00004537509,0.00003992531,0.00002021689,0.0005366816,0.00001555769,0.0008624535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002490257,"threshold_uncertainty_score":0.004951596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03318811651424976,"score_gpt":0.2365695645883045,"score_spread":0.2033814480740548,"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."}}