{"id":"W4312178000","doi":"10.18280/ria.360508","title":"Prediction of Seizure in the EEG Signal with Time Aware Recurrent Neural Network","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ictal; Recurrent neural network; Computer science; Artificial intelligence; Convolutional neural network; Electroencephalography; Epilepsy; Pattern recognition (psychology); Deep learning; Support vector machine; Epileptic seizure; Feature (linguistics); Artificial neural network; Machine learning; Neuroscience; Psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.0004906922,0.0001354077,0.0001648643,0.00007336358,0.000264439,0.00003954064,0.0006206324,0.00002701666,0.0004818731],"category_scores_gemma":[0.00003203185,0.00009775802,0.00006372554,0.0008224067,0.0001147775,0.0001040645,0.000146898,0.0004039746,0.00003597283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003581128,"about_ca_system_score_gemma":0.0000272669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001195842,"about_ca_topic_score_gemma":0.000005687605,"domain_scores_codex":[0.9982469,0.000368072,0.0003662012,0.0003787794,0.0003406686,0.0002993667],"domain_scores_gemma":[0.9990656,0.0004028358,0.000144632,0.0003273133,0.00002632155,0.00003324796],"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":[0.0001276572,0.0003220913,0.001535634,0.00003453363,0.000005129024,0.0000573357,0.00473792,0.9591629,0.01636482,0.0006934792,0.004225148,0.01273338],"study_design_scores_gemma":[0.00006469723,0.001040679,0.0005246126,0.00008309133,0.000009663809,0.0001995093,0.001565607,0.9508754,0.03865277,0.0004435671,0.00638355,0.0001568755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990362,0.0001529018,0.0056944,0.001182786,0.0004614208,0.0005546662,0.00005915518,0.00006488354,0.001467777],"genre_scores_gemma":[0.9989721,0.00001000724,0.0000552489,0.0003439205,0.00007316715,0.00005295728,0.000007326593,0.00001210722,0.0004732236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02228795,"threshold_uncertainty_score":0.5276172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05210197904401229,"score_gpt":0.2605902429792897,"score_spread":0.2084882639352774,"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."}}