{"id":"W4408026899","doi":"10.18280/ts.420134","title":"An Amplitude Differentiation Model Using Deep Learning for Early Diagnosis of Epilepsy Using EEG Signals","year":2025,"lang":"en","type":"article","venue":"Traitement du signal","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Electroencephalography; Epilepsy; Amplitude; Artificial intelligence; Computer science; Deep learning; Pattern recognition (psychology); Speech recognition; Neuroscience; Psychology; Physics; Optics","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":[0.0003635251,0.0004186789,0.0004599537,0.0003020634,0.0001599122,0.0004256847,0.0005469277,0.0006389911,0.001043954],"category_scores_gemma":[0.0007966939,0.0002269518,0.0004358256,0.0002822326,0.0001540158,0.0004018461,0.0003832834,0.0009013265,0.0002942718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002851955,"about_ca_system_score_gemma":0.0005418807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005290194,"about_ca_topic_score_gemma":0.005753677,"domain_scores_codex":[0.9999274,0.00001462154,0.000005399068,0.00002205205,0.0000150854,0.00001542061],"domain_scores_gemma":[0.9997928,0.000107873,0.0000170695,0.0000104364,0.00006030501,0.00001163859],"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":[0.0002942818,0.0001930645,0.002194939,0.0001147017,0.0001017757,0.000128389,0.00004460987,0.6630557,0.01520823,0.00403795,0.002589367,0.3120369],"study_design_scores_gemma":[0.000002943139,0.00001467158,0.0001383065,0.000003179204,0.000006112651,0.00001149828,0.000001142361,0.9987656,0.0005304034,0.0004261531,0.00009823979,0.000001829938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05888251,0.001140459,0.9371495,0.0004535598,0.0001051294,0.00003177853,0.0001608155,0.0006061578,0.001470132],"genre_scores_gemma":[0.9035167,0.0005991757,0.09059963,0.0001954011,0.00007405775,0.00006585552,0.0003398277,0.00003859804,0.004570737],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005290194,"threshold_uncertainty_score":0.01051879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05792084053315565,"score_gpt":0.3181710821071213,"score_spread":0.2602502415739656,"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."}}