{"id":"W2039402146","doi":"10.1115/1.1839592","title":"Monte Carlo Simulation of Moment Lyapunov Exponents","year":2005,"lang":"en","type":"article","venue":"Journal of Applied Mechanics","topic":"Quantum chaos and dynamical systems","field":"Physics and Astronomy","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Monte Carlo method; Lyapunov exponent; Moment (physics); Statistical physics; Noise (video); Bounded function; Second moment of area; Mathematics; Applied mathematics; Physics; Mathematical analysis; Computer science; Classical mechanics; Nonlinear system; Geometry; Quantum mechanics","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":[0.0002302655,0.0001023644,0.0002752329,0.0000593035,0.00002932439,0.00001254079,0.0001198314,0.00003860767,0.00007954652],"category_scores_gemma":[0.000001355896,0.00008274872,0.0001333581,0.0000767877,0.000004952999,0.0000760052,0.00002663215,0.0001249636,0.000008380566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004460836,"about_ca_system_score_gemma":0.00002394576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009406621,"about_ca_topic_score_gemma":8.504141e-7,"domain_scores_codex":[0.9989128,0.00001102397,0.0005607913,0.00008021322,0.0002981489,0.0001370035],"domain_scores_gemma":[0.999089,0.00003117584,0.0005749047,0.0001142278,0.0001043042,0.00008640379],"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":[0.0001925294,0.0004083387,0.0001286626,0.00002615034,0.0001741549,0.000001201184,0.0006384604,0.8282947,0.01663001,0.1125511,0.0001492499,0.04080541],"study_design_scores_gemma":[0.001691918,0.0001699049,0.00005601034,0.00005952761,0.00007355807,0.000001502365,0.0006672611,0.9680238,0.006980485,0.01419803,0.007888348,0.0001896517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7987905,0.00004442729,0.1994967,0.00005379719,0.0002268945,0.0001524927,0.00001125818,0.000005331542,0.001218533],"genre_scores_gemma":[0.9981749,0.00000273204,0.001279775,0.00001802319,0.0004653895,0.000002367824,9.609817e-7,0.00001231186,0.00004354118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1993844,"threshold_uncertainty_score":0.3374395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00932931523478038,"score_gpt":0.237807896893037,"score_spread":0.2284785816582566,"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."}}