{"id":"W3162952110","doi":"10.18280/ts.380210","title":"Seizure Detection Based on Adaptive Feature Extraction by Applying Extreme Learning Machines","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Extreme learning machine; Pattern recognition (psychology); Artificial intelligence; Preprocessor; Computer science; Electroencephalography; Ictal; Feature extraction; Parseval's theorem; Signal processing; Epileptic seizure; Speech recognition; Mathematics; Artificial neural network; Radar; Short-time Fourier transform; Psychology; Fourier transform; Neuroscience","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":[0.0005324919,0.0004780347,0.0004571347,0.0009235581,0.0001964471,0.000468071,0.0003417483,0.0004357629,0.0006542475],"category_scores_gemma":[0.001587593,0.000139227,0.0004290851,0.0006767339,0.0002409528,0.0006136549,0.0003437138,0.0003874632,0.0002271397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001894521,"about_ca_system_score_gemma":0.0001539586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004648764,"about_ca_topic_score_gemma":0.0004150961,"domain_scores_codex":[0.9996929,0.00008191884,0.00003165444,0.00006626724,0.00009468404,0.00003247998],"domain_scores_gemma":[0.9995978,0.0002215111,0.0000541306,0.00003117969,0.00008534248,0.00001005722],"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":[0.0003420764,0.0002235179,0.007977041,0.000153651,0.0001172204,0.0004360299,0.0002003639,0.1463983,0.100039,0.002736039,0.001002852,0.7403739],"study_design_scores_gemma":[0.00001050413,0.0001401213,0.006061532,0.00001301702,0.00002045885,0.0002464846,0.00003013179,0.9697505,0.02104328,0.002023445,0.0006404871,0.00002002495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1163153,0.0002308012,0.8815558,0.0001097833,0.00002555315,0.00005040256,0.00005024078,0.0007393793,0.0009228568],"genre_scores_gemma":[0.8319261,0.0001125512,0.1670175,0.00003471054,0.00001690344,0.00005719581,0.0001022455,0.00002982856,0.0007030503],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0009235581,"threshold_uncertainty_score":0.002816141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03255329160028756,"score_gpt":0.2584865941663499,"score_spread":0.2259333025660624,"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."}}