{"id":"W4285111878","doi":"10.1109/access.2022.3176367","title":"An Interpretable Deep Learning Classifier for Epileptic Seizure Prediction Using EEG Data","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"U.S. Department of Commerce","keywords":"Computer science; Artificial intelligence; Deep learning; Electroencephalography; Epileptic seizure; Classifier (UML); Pattern recognition (psychology); Artificial neural network; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005752095,0.0006052491,0.0003398595,0.0004500689,0.0002088321,0.000643085,0.0005263734,0.0009253712,0.001134769],"category_scores_gemma":[0.002552535,0.000191662,0.0003267472,0.0003741928,0.0002731924,0.0006757192,0.0004489402,0.001063379,0.000326984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004376401,"about_ca_system_score_gemma":0.000532194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001553344,"about_ca_topic_score_gemma":0.001982764,"domain_scores_codex":[0.9997839,0.00004705277,0.00001746084,0.00005831453,0.00006669288,0.0000265028],"domain_scores_gemma":[0.9995779,0.0001911952,0.00004572343,0.00005088263,0.0001200093,0.00001417659],"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":[0.000275771,0.000282175,0.004932352,0.0001316481,0.00008224379,0.0006247378,0.000175207,0.4315132,0.05410547,0.01657972,0.005459289,0.4858381],"study_design_scores_gemma":[0.000006605318,0.00004466533,0.0004326096,0.00001008408,0.000008304202,0.00003765088,0.00001076421,0.9913163,0.004251624,0.003297314,0.0005782894,0.000005793376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0815825,0.0004497671,0.9131337,0.0009548176,0.0001017561,0.00009940237,0.0004307178,0.001125112,0.002122133],"genre_scores_gemma":[0.792493,0.0003167345,0.2026862,0.0002411452,0.00008587896,0.000134831,0.0007066461,0.00004091365,0.003294638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001553344,"threshold_uncertainty_score":0.00379622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1301660978695224,"score_gpt":0.3729569014518458,"score_spread":0.2427908035823234,"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."}}