{"id":"W2913040985","doi":"10.1109/tie.2018.2890486","title":"Displacement and Force Self-Sensing Technique for Piezoelectric Actuators Using a Nonlinear Constitutive Model","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Electronics","topic":"Piezoelectric Actuators and Control","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Displacement (psychology); Nonlinear system; Hysteresis; Actuator; Control theory (sociology); Piezoelectricity; Capacitance; Voltage; Physics; Engineering; Acoustics; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002305767,0.0003527695,0.0003900731,0.0002747932,0.000220013,0.00005784107,0.0001188065,0.0003842594,0.000008550424],"category_scores_gemma":[0.000009178322,0.0003682392,0.000141596,0.0004379233,0.00003173304,0.0001810961,0.000001349526,0.0007671698,0.000004090931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000731812,"about_ca_system_score_gemma":0.0004724717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000113849,"about_ca_topic_score_gemma":0.00001080245,"domain_scores_codex":[0.9983352,0.00002725721,0.000349726,0.0003786926,0.0002042133,0.000704893],"domain_scores_gemma":[0.9993113,0.000173757,0.00007078263,0.0002470947,0.00006650935,0.0001305115],"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":[0.0005149299,0.0001419942,0.000004245035,0.00005404952,0.0005311758,0.000001559324,0.0001589929,0.5767244,0.0176024,0.00135083,0.0001081886,0.4028072],"study_design_scores_gemma":[0.002049385,0.0004596351,2.561679e-8,0.00003853969,0.0001969384,0.00002405445,0.00001802749,0.9510068,0.0450141,0.0002280391,0.0005831154,0.0003812924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04928992,0.0001573424,0.947755,0.00002285211,0.0003354111,0.001931125,0.00005682855,0.0002778726,0.0001736805],"genre_scores_gemma":[0.9934576,0.0001894181,0.005935131,0.00005204582,0.0001072469,0.0001010925,0.000004574887,0.00007420833,0.0000786898],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9441677,"threshold_uncertainty_score":0.999877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01358665333531682,"score_gpt":0.2227391785396345,"score_spread":0.2091525252043176,"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."}}