{"id":"W2132635701","doi":"10.1109/isic.2002.1157754","title":"Contact task stability analysis via Lyapunov exponents","year":2003,"lang":"en","type":"article","venue":"","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Lyapunov exponent; Control theory (sociology); Nonlinear system; Lyapunov function; Stability (learning theory); Controller (irrigation); Lyapunov stability; Lyapunov redesign; Robotics; Lyapunov equation; Mathematics; Computer science; Robot; Artificial intelligence; Control (management); Physics","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":[0.0002580865,0.0001144344,0.0002670261,0.00005052158,0.00002383644,0.00002806739,0.00009300834,0.00006126554,0.0006073585],"category_scores_gemma":[0.00001748168,0.00009699314,0.000167253,0.0002693904,0.000003687323,0.00005633102,0.000007554429,0.00006966187,0.00007515032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007884338,"about_ca_system_score_gemma":0.000004925108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008636364,"about_ca_topic_score_gemma":0.0002249938,"domain_scores_codex":[0.9992086,0.00003844259,0.0002444214,0.0001528735,0.0001475352,0.0002081077],"domain_scores_gemma":[0.9995396,0.00003748147,0.00001853557,0.0002756923,0.00002488916,0.0001038396],"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":[0.00008961192,0.0008520552,0.09956878,0.0002963445,0.01362857,0.00006270902,0.000574147,0.0647708,0.5375798,0.2540413,0.00135411,0.0271818],"study_design_scores_gemma":[0.0007818363,0.00004480014,0.007837993,0.00000457232,0.0003012101,0.000001811841,0.00007684928,0.9814875,0.002136763,0.001694727,0.005244426,0.000387502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3478303,0.0001121829,0.6263286,0.00001371169,0.0002900182,0.0001467901,0.000008026032,0.0002289319,0.02504144],"genre_scores_gemma":[0.9994423,0.000004282,0.0003360449,0.0000297619,0.00001451017,0.00001312531,0.000005357501,0.00001234404,0.0001422202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9167167,"threshold_uncertainty_score":0.665015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006871700670406339,"score_gpt":0.1846269546643976,"score_spread":0.1777552539939913,"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."}}