{"id":"W2018946478","doi":"10.1109/iembs.2010.5626781","title":"A novel morphology-based classifier for automatic detection of epileptic seizures","year":2010,"lang":"en","type":"article","venue":"","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Electroencephalography; Rhythm; Epilepsy; Epileptic seizure; Pattern recognition (psychology); Computer science; Classifier (UML); Artificial intelligence; Neuroscience; Medicine; Psychology; Internal 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006672639,0.0005630793,0.0008907536,0.001768458,0.0003508621,0.000808525,0.0009013952,0.001268823,0.001883908],"category_scores_gemma":[0.002613588,0.0002785717,0.0005719709,0.001134022,0.0002635027,0.001017348,0.0004326078,0.0006580245,0.001625913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003502668,"about_ca_system_score_gemma":0.000630426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001398895,"about_ca_topic_score_gemma":0.001815715,"domain_scores_codex":[0.9992866,0.00007814207,0.00007600807,0.0001483453,0.0003575819,0.00005330849],"domain_scores_gemma":[0.9987544,0.0003518727,0.000100224,0.0001009292,0.0006286818,0.00006397417],"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":[0.0002311626,0.0001426647,0.003498378,0.0001313455,0.00006865893,0.0003515815,0.00004590451,0.008818799,0.1355105,0.001119927,0.00649549,0.8435857],"study_design_scores_gemma":[0.00007883929,0.0004899318,0.01298776,0.00004240591,0.00009637656,0.002829874,0.0000479905,0.8882421,0.07543617,0.002170743,0.01749112,0.00008668685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03531895,0.0007904825,0.9585108,0.0002356538,0.0002126113,0.0001908913,0.0004327903,0.002875192,0.001432669],"genre_scores_gemma":[0.2016099,0.000543859,0.7914782,0.0002483448,0.0001930929,0.0003157003,0.001208101,0.0001356403,0.004267217],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001883908,"threshold_uncertainty_score":0.006302238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03581067018648912,"score_gpt":0.2844795135890069,"score_spread":0.2486688434025178,"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."}}