{"id":"W4295431422","doi":"10.1016/j.yebeh.2022.108906","title":"Personalized model to predict seizures based on dynamic and static continuous EEG monitoring data","year":2022,"lang":"en","type":"article","venue":"Epilepsy & Behavior","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Epilepsy; Electroencephalography; Cohort; Medicine; Retrospective cohort study; Recurrent neural network; Artificial intelligence; Machine learning; Computer science; Artificial neural network; Internal medicine; Psychiatry","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":[0.0002563499,0.0002105445,0.0002375678,0.0001422448,0.0003597961,0.0001287049,0.0008364931,0.00003051425,0.0001070526],"category_scores_gemma":[0.0001129678,0.0002062702,0.00004248802,0.0001791378,0.00007636249,0.0001595531,0.0006132153,0.0003123434,0.00001160745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008775097,"about_ca_system_score_gemma":0.00006884339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004455139,"about_ca_topic_score_gemma":0.000004708364,"domain_scores_codex":[0.9977927,0.0001878316,0.0002426545,0.0008215674,0.0005517693,0.0004035287],"domain_scores_gemma":[0.9987644,0.0002487644,0.00007861271,0.0007121431,0.00001647103,0.0001795874],"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":[0.001064396,0.002520802,0.06172248,0.00009976057,0.00002595714,0.001342592,0.007593395,0.09247713,0.7309974,0.0001343691,0.01463133,0.08739039],"study_design_scores_gemma":[0.001594137,0.001041654,0.02194131,0.00007979686,0.00009183741,0.0000704061,0.0005287688,0.9633123,0.008530275,0.00003324941,0.002240612,0.0005356374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952005,0.00003684867,0.001995178,0.0003421875,0.0005600569,0.0005652938,0.001024536,0.0001587628,0.00011664],"genre_scores_gemma":[0.9957615,0.00000478567,0.001755486,0.0009531471,0.00003480069,0.0002199983,0.00003452538,0.00003803874,0.001197704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8708352,"threshold_uncertainty_score":0.8411456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05723566951068926,"score_gpt":0.3272195278046039,"score_spread":0.2699838582939146,"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."}}