{"id":"W2072473279","doi":"10.1142/s0129065711002894","title":"RESPONSIVE NEUROMODULATORS BASED ON ARTIFICIAL NEURAL NETWORKS USED TO CONTROL SEIZURE-LIKE EVENTS IN A COMPUTATIONAL MODEL OF EPILEPSY","year":2011,"lang":"en","type":"article","venue":"International Journal of Neural Systems","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; McMaster University","keywords":"Neuromodulation; Ictal; Deep brain stimulation; Epilepsy; Neuroscience; Hippocampal formation; Computer science; Artificial neural network; Modulation (music); Electroencephalography; Stimulation; Artificial intelligence; Medicine; Psychology; Physics; Internal medicine; Parkinson's disease","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004701118,0.0002284001,0.0004364118,0.0006691151,0.00004161705,0.00005089417,0.0008620331,0.00007944001,0.00001263412],"category_scores_gemma":[0.0003214717,0.0001933207,0.0002110632,0.0002514872,0.00005853261,0.0002914454,0.00006090509,0.0003771052,0.000005050806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001058766,"about_ca_system_score_gemma":0.00008245173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004201639,"about_ca_topic_score_gemma":0.000009610327,"domain_scores_codex":[0.9965891,0.0005398873,0.001171223,0.0003227041,0.001106863,0.000270225],"domain_scores_gemma":[0.9977136,0.0007461697,0.0007807887,0.0001593835,0.0004342672,0.0001657762],"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":[0.002207928,0.0002710691,0.004662304,0.000006232004,0.00002318355,0.0002067672,0.0004196884,0.9756342,0.01575425,0.0004312927,0.0001099087,0.0002731701],"study_design_scores_gemma":[0.001353927,0.0006789368,0.008676378,0.000167283,0.000009231413,0.000189373,0.00003247207,0.9856082,0.002823955,0.000295799,0.00001122184,0.0001532786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618616,0.000009325435,0.03308792,0.0007976498,0.003803149,0.0003261638,0.00005281611,0.00001679253,0.00004460815],"genre_scores_gemma":[0.9980783,4.660421e-7,0.0001891056,0.001431199,0.0002460851,0.000008202553,0.00000181939,0.00002397668,0.0000208279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03621674,"threshold_uncertainty_score":0.7883391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07158444133523344,"score_gpt":0.2971408655060035,"score_spread":0.2255564241707701,"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."}}