{"id":"W2144224451","doi":"10.1109/robot.1997.620045","title":"Stability of control for the Preisach hysteresis model","year":2002,"lang":"en","type":"article","venue":"","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Hysteresis; Actuator; Control theory (sociology); Passivity; Preisach model of hysteresis; Stability (learning theory); Magnetic hysteresis; Simple (philosophy); Smart material; Identification (biology); Shape-memory alloy; Control (management); Control engineering; Computer science; Engineering; Materials science; Physics; Magnetization; Condensed matter physics; Artificial intelligence; Magnetic field","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001584771,0.00003510613,0.00006797387,0.0000031917,0.00006585532,0.00001338787,0.0001645184,0.00001338492,0.002604998],"category_scores_gemma":[0.00003283038,0.00001794921,0.0000301213,0.0000199107,0.0000633651,0.00002554377,0.00001752379,0.000011056,0.00001970219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004030717,"about_ca_system_score_gemma":0.000005069034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005164662,"about_ca_topic_score_gemma":0.00001225077,"domain_scores_codex":[0.9996215,0.00001054793,0.0001264617,0.00009205657,0.00006384916,0.00008562514],"domain_scores_gemma":[0.9995056,0.0001269859,0.00003115625,0.0002710671,0.00004900564,0.00001619649],"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":[0.00003079738,0.0001479984,0.00007235538,0.0000585654,0.000005535664,8.230843e-9,0.0003654262,0.00141281,0.9576403,0.02910815,0.006330552,0.004827456],"study_design_scores_gemma":[0.0003048731,0.00004013789,0.0000823154,0.000001688018,0.00001818711,1.539738e-7,0.00007876935,0.8629264,0.1335623,0.001235803,0.001704337,0.00004506512],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5177101,0.0003536307,0.4612178,0.005317612,0.00004697055,0.001342832,0.000135071,0.00004916168,0.01382676],"genre_scores_gemma":[0.9952137,0.000004627905,0.002863644,0.0001458202,0.00001103767,0.0001846793,1.74104e-7,0.000002646981,0.001573665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8615136,"threshold_uncertainty_score":0.9983068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06404116304099206,"score_gpt":0.2379859554896853,"score_spread":0.1739447924486932,"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."}}