{"id":"W4408040876","doi":"10.18280/ts.420114","title":"Effectiveness of Multi Input Data and a Novel CNN Model for Epilepsy Classification","year":2025,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Epilepsy; Computer science; Artificial intelligence; Pattern recognition (psychology); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006124289,0.0001026223,0.0001393191,0.0001110663,0.0001159453,0.00003069991,0.0002663072,0.00004795511,0.000008548468],"category_scores_gemma":[0.0002388848,0.00009935754,0.00003124993,0.0002006217,0.0001060938,0.0001759213,0.00006606436,0.00006607651,0.000001505301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003557983,"about_ca_system_score_gemma":0.00006070769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003272883,"about_ca_topic_score_gemma":0.000002952428,"domain_scores_codex":[0.9989247,0.00009303627,0.0002586714,0.0004605422,0.0001374655,0.0001256174],"domain_scores_gemma":[0.9990232,0.0004509928,0.0001153662,0.0003190802,0.00005596421,0.00003539115],"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":[0.0002030911,0.0002631302,0.0002513389,0.0002123757,0.000008052696,8.335772e-8,0.0000746271,0.0004297097,0.9641985,0.0265218,0.0000781398,0.007759206],"study_design_scores_gemma":[0.00148339,0.00004603084,0.01879457,0.00005041057,0.00002315836,0.000001091007,0.00003639052,0.8175432,0.1611488,0.0005210848,0.0002746371,0.00007724689],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1423649,0.00001250439,0.8560851,0.0002743756,0.00008643337,0.0007397623,0.0001764698,0.0000431799,0.0002173108],"genre_scores_gemma":[0.9977791,0.000007667958,0.001672218,0.0001673773,0.00001353337,0.0001554325,0.00003683281,0.000008941374,0.0001589045],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8554142,"threshold_uncertainty_score":0.4051683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1247727598836317,"score_gpt":0.3334797254940197,"score_spread":0.2087069656103879,"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."}}