{"id":"W2157617740","doi":"10.1109/tbme.2004.831520","title":"Control of State Transitions in an In Silico Model of Epilepsy Using Small Perturbations","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Artificial neural network; Chaotic; Nonlinear system; Gaussian; Control theory (sociology); Perturbation (astronomy); Computer science; State variable; Topology (electrical circuits); Physics; Mathematics; Artificial intelligence; Control (management)","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":[0.0003253971,0.0004488261,0.000378125,0.000182855,0.0002812288,0.0004969005,0.0005339832,0.0006756078,0.0009032488],"category_scores_gemma":[0.0009741473,0.0002279168,0.0003943859,0.00008350424,0.000850924,0.000451402,0.0005093225,0.0005293689,0.00008087419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005045672,"about_ca_system_score_gemma":0.0004631439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005159457,"about_ca_topic_score_gemma":0.002910998,"domain_scores_codex":[0.9998721,0.00004591016,0.000007947576,0.00002870117,0.00002885709,0.00001641612],"domain_scores_gemma":[0.9996827,0.000145684,0.00008144462,0.0000248461,0.00003785172,0.0000275582],"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":[0.00005357907,0.00002432275,0.0003122217,0.00002078516,0.00001537772,0.00007065871,0.0000380656,0.9859467,0.008565334,0.003810398,0.00006810084,0.001074416],"study_design_scores_gemma":[0.000009905877,0.00002680483,0.00007610569,0.000001389449,0.000004090179,0.000004665886,0.000002936026,0.9982844,0.0009483699,0.0005660392,0.00007168858,0.000003586443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5688971,0.0001405227,0.4224678,0.0007120147,0.000112455,0.0001083625,0.0001581715,0.0004544523,0.006949063],"genre_scores_gemma":[0.9921354,0.00006017472,0.006391964,0.00003016613,0.000007791106,0.00006941284,0.00002689874,0.00001045581,0.001267765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005159457,"threshold_uncertainty_score":0.01025885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02786735257680981,"score_gpt":0.2357986696350776,"score_spread":0.2079313170582678,"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."}}