{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003308765,0.000685857,0.0003844057,0.0004492925,0.0001236721,0.0003809733,0.0003796063,0.0003238385,0.000525403],"category_scores_gemma":[0.0009441081,0.0001883255,0.0004544816,0.0002791982,0.0001189941,0.0003938105,0.0002468376,0.0004581176,0.0001753862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003337894,"about_ca_system_score_gemma":0.00034412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01088826,"about_ca_topic_score_gemma":0.01047001,"domain_scores_codex":[0.9998668,0.00001949951,0.00001257975,0.00004333882,0.00003665312,0.000020979],"domain_scores_gemma":[0.9998294,0.00005544857,0.00003134674,0.00001144282,0.00006286702,0.000009503944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003815525,0.0001838293,0.01381349,0.000134227,0.0001724734,0.0005130223,0.00006888236,0.6285505,0.02341298,0.0009675983,0.004229965,0.3275715],"study_design_scores_gemma":[0.000001759875,0.00001536301,0.0007567435,0.000002238071,0.000007239403,0.00001685231,0.00000305188,0.9980375,0.0009689675,0.0001137032,0.00007412753,0.000002555156],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4182096,0.003214357,0.5719157,0.0005645972,0.0002227948,0.00007945503,0.0006020954,0.00219542,0.002996079],"genre_scores_gemma":[0.9705122,0.0008572596,0.02625251,0.00005351535,0.00004912254,0.00003528776,0.000555143,0.00002853409,0.001656356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01088826,"threshold_uncertainty_score":0.02164972,"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."}}