{"id":"W3144738685","doi":"10.18280/ts.380107","title":"Signal Dynamics Analysis for Epileptic Seizure Classification on EEG Signals","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universitas Telkom","keywords":"Electroencephalography; Ictal; Epilepsy; Pattern recognition (psychology); Computer science; Artificial intelligence; Epileptic seizure; Speech recognition; Naive Bayes classifier; SIGNAL (programming language); Psychology; Neuroscience; Support vector machine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003660432,0.0002879123,0.00038028,0.0002668218,0.000266855,0.000234546,0.0003932991,0.0001070841,0.00125004],"category_scores_gemma":[0.00008653291,0.0002666982,0.0003938702,0.0008608852,0.00008695469,0.0001818978,0.00005563498,0.0001942161,0.00007926866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001432301,"about_ca_system_score_gemma":0.00008661298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003424382,"about_ca_topic_score_gemma":0.00002761422,"domain_scores_codex":[0.9973539,0.0002428,0.000530124,0.000862145,0.0005554293,0.0004556587],"domain_scores_gemma":[0.9982988,0.0008641757,0.0002106559,0.0003278815,0.0001533059,0.0001451993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002612663,0.001124187,0.001675849,0.00009510243,0.0004705759,0.00007788582,0.0006050073,0.03754554,0.9146357,0.02283077,0.004320696,0.01635738],"study_design_scores_gemma":[0.001085793,0.0006462633,0.007369252,0.00005377315,0.0004210591,0.00001485165,0.0002768427,0.6888639,0.296289,0.001294136,0.003187404,0.0004977661],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6625761,0.00003792096,0.3312273,0.002706404,0.0002629349,0.0006041339,0.0003344016,0.0001738172,0.002076997],"genre_scores_gemma":[0.9952493,0.000008980352,0.001052594,0.002215677,0.0001899847,0.00009636586,0.0001667113,0.00002863829,0.0009916902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6513183,"threshold_uncertainty_score":0.9999785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05182252665127585,"score_gpt":0.2932550666738257,"score_spread":0.2414325400225499,"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."}}