{"id":"W4386074562","doi":"10.11159/eee23.145","title":"Early Epileptic Seizure Prediction Using EEG Signals with Machine Learning","year":2023,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electroencephalography; Epileptic seizure; Computer science; Epilepsy; Artificial intelligence; Speech recognition; Machine learning; Pattern recognition (psychology); Psychology; Neuroscience","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":[0.0003337443,0.0006916156,0.0005466231,0.001543862,0.0001272129,0.0005294391,0.0002861466,0.0004160812,0.001007396],"category_scores_gemma":[0.001588974,0.00009580522,0.0004463575,0.001083674,0.00009578037,0.0004864294,0.0002978136,0.0004521516,0.0006610136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001612274,"about_ca_system_score_gemma":0.0002557059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002142197,"about_ca_topic_score_gemma":0.00196768,"domain_scores_codex":[0.9997764,0.00003743494,0.0000322867,0.00005756709,0.00005939532,0.00003696996],"domain_scores_gemma":[0.999586,0.0001788693,0.00006491688,0.0000313711,0.000119094,0.0000197611],"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":[0.0008380386,0.000551296,0.05896457,0.0003410938,0.0001993742,0.0008102526,0.00007580494,0.09113614,0.01808663,0.0006722389,0.007270824,0.8210537],"study_design_scores_gemma":[0.00002895833,0.0003768755,0.053634,0.00008664987,0.00007332835,0.0006563931,0.000110192,0.9266984,0.0135368,0.001571435,0.003190095,0.00003690527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6614448,0.004180629,0.3189431,0.0006153383,0.000381382,0.0002383449,0.005461931,0.003470747,0.0052637],"genre_scores_gemma":[0.9443267,0.001090847,0.04900684,0.00004090597,0.00009730138,0.00008383473,0.003908253,0.00002818441,0.00141718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002142197,"threshold_uncertainty_score":0.004259467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01333949900705959,"score_gpt":0.2166865015751461,"score_spread":0.2033470025680865,"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."}}