{"id":"W4292874177","doi":"10.1109/memea54994.2022.9856458","title":"Epileptic Seizure Detection Using Convolution Neural Networks","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Epilepsy; Convolution (computer science); Computer science; Artificial neural network; Pattern recognition (psychology); Artificial intelligence; Population; Electroencephalography; Scalp; Convolutional neural network; Epileptic seizure; Neuroscience; Psychology; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005897096,0.0001982079,0.000163309,0.0001356527,0.0008071799,0.0001020416,0.0005849941,0.00007783519,0.0005992759],"category_scores_gemma":[0.00009065741,0.0001952664,0.00008307273,0.0003410265,0.0001296467,0.0001444598,0.0001997733,0.00055787,0.00001362626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000297029,"about_ca_system_score_gemma":0.00003523553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003628315,"about_ca_topic_score_gemma":0.00001123468,"domain_scores_codex":[0.9967116,0.0002470259,0.0004079106,0.0006387361,0.00170881,0.0002859395],"domain_scores_gemma":[0.9991332,0.0001673699,0.0001912023,0.0002341927,0.00007942287,0.0001946625],"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":[0.0002738159,0.00130058,0.002096585,0.00003447294,0.0001388816,0.00003000295,0.0002285402,0.2017519,0.7151887,0.002919395,0.002037265,0.07399994],"study_design_scores_gemma":[0.0008848431,0.0002281542,0.0002932855,0.00002675213,0.00003188822,0.0001821464,0.00006990288,0.9411917,0.02312737,0.0002672384,0.03339332,0.0003033429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8393456,0.0001484324,0.1422875,0.007087586,0.005889693,0.001496225,0.0001097362,0.0002926447,0.003342533],"genre_scores_gemma":[0.9954258,0.00003784371,0.00004952896,0.003049144,0.0007271183,0.000456069,0.00002100262,0.00002380071,0.0002096771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7394399,"threshold_uncertainty_score":0.7962734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05316991573580523,"score_gpt":0.3031245750167617,"score_spread":0.2499546592809565,"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."}}