{"id":"W2975639659","doi":"10.1007/s12555-019-0276-1","title":"Stability of Stochastic Functional Differential Systems with Semi-Markovian Switching and Lévy Noise and Its Application","year":2019,"lang":"en","type":"article","venue":"International Journal of Control Automation and Systems","topic":"Neural Networks Stability and Synchronization","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Stability (learning theory); Mathematics; Control theory (sociology); Noise (video); Applied mathematics; Lyapunov function; Controller (irrigation); Markov process; Stochastic differential equation; Moment (physics); Diagonal; Exponential stability; Computer science; Nonlinear system; Physics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005565425,0.0001143071,0.0002847712,0.000112737,0.00005315082,0.000215058,0.0001710234,0.00005524407,0.000004900766],"category_scores_gemma":[0.00004767013,0.00008696508,0.00003048526,0.00007956152,0.00002671192,0.0007504454,0.00003897707,0.0001105332,7.086157e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005598482,"about_ca_system_score_gemma":0.00005612204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002411205,"about_ca_topic_score_gemma":0.000005673829,"domain_scores_codex":[0.9984321,0.0001547181,0.0005849379,0.0001909753,0.0005449789,0.00009229804],"domain_scores_gemma":[0.9981727,0.0002671127,0.0006703651,0.000109841,0.0007008046,0.00007918846],"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":[0.002692507,0.0007747109,0.1999626,0.002150905,0.001729702,0.00002168125,0.005658354,0.2842492,0.1953795,0.2491525,0.00006403084,0.05816437],"study_design_scores_gemma":[0.0016649,0.0001462216,0.04110111,0.0001705225,0.00001947275,0.0002142753,0.00009434424,0.9563101,0.0000494018,0.0001244809,0.00001950021,0.00008566533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4945517,0.0003675578,0.5041648,0.000189818,0.0004569823,0.0002387707,0.000004627332,0.00001159707,0.00001422428],"genre_scores_gemma":[0.9997372,0.0000153824,0.00006198532,0.00001934794,0.0001395801,0.000008395605,0.000003568752,0.000005097048,0.000009434439],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6720609,"threshold_uncertainty_score":0.3546333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007155737310393918,"score_gpt":0.2067468944509359,"score_spread":0.199591157140542,"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."}}