{"id":"W2073335387","doi":"10.1117/12.444090","title":"Discrete-time compensation algorithm for hysteresis in piezoceramic actuators","year":2001,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Actuator; Hysteresis; Compensation (psychology); Control theory (sociology); Displacement (psychology); Discrete time and continuous time; Voltage; Computer science; Algorithm; Engineering; Mathematics; 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":[0.0005834261,0.0002504387,0.0003682949,0.00008691555,0.00009727439,0.0001343987,0.0008078402,0.0001373601,0.0000587102],"category_scores_gemma":[0.0002497186,0.00020297,0.0003492846,0.0002639198,0.0001792108,0.000420566,0.0001285317,0.0001401065,0.000006319355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001454397,"about_ca_system_score_gemma":0.00002873627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002540058,"about_ca_topic_score_gemma":4.2045e-7,"domain_scores_codex":[0.9980975,1.732765e-8,0.0006713842,0.0003886808,0.0004510334,0.0003913962],"domain_scores_gemma":[0.9985698,0.0001482464,0.0003090846,0.00006491841,0.000817697,0.00009028504],"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":[0.00007227096,0.0001226759,0.0001221422,0.0001949936,0.00005920661,3.822764e-8,0.0001838087,0.00005630866,0.8475722,0.146806,0.001281996,0.003528343],"study_design_scores_gemma":[0.00360576,0.0008681545,0.002226973,0.0006235291,0.0002492027,0.00002959644,0.002718718,0.5218296,0.4449837,0.007121677,0.01470433,0.001038825],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945105,0.0000495894,0.0007794041,0.00215885,0.0001318532,0.0009217408,0.00009025836,0.00006711028,0.001290747],"genre_scores_gemma":[0.7088751,0.00008403837,0.2890112,0.0001477596,0.0004147393,0.000706662,0.00002491952,0.0000725143,0.0006631074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5217733,"threshold_uncertainty_score":0.8276875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01104940974411905,"score_gpt":0.2280371776910495,"score_spread":0.2169877679469304,"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."}}