{"id":"W3208813259","doi":"10.1515/teme-2021-0080","title":"A simple closed-form model to accurately calculate the electromechanical coupling coefficient of CMUTs","year":2021,"lang":"en","type":"article","venue":"tm - Technisches Messen","topic":"Ultrasonics and Acoustic Wave Propagation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Electromechanical coupling coefficient; Nonlinear system; Capacitive micromachined ultrasonic transducers; Diaphragm (acoustics); Finite element method; Transducer; Coupling coefficient of resonators; Stiffness; Spring (device); Materials science; Acoustics; Mechanics; Softening; Residual stress; Coupling (piping); Structural engineering; Piezoelectricity; Physics; Engineering; Vibration; Composite material; Resonator","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":[],"consensus_categories":[],"category_scores_codex":[0.0002543784,0.0001538613,0.0002085926,0.00004741646,0.00008040989,0.00003936419,0.0002129215,0.0000942957,0.00001894755],"category_scores_gemma":[0.00009204398,0.0001218958,0.00007277277,0.0003689895,0.00002076215,0.00005358055,0.00008320802,0.000214939,0.00001253579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000541102,"about_ca_system_score_gemma":0.00006821452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005256122,"about_ca_topic_score_gemma":0.000005832804,"domain_scores_codex":[0.9989563,0.00000716847,0.0002899525,0.0001930502,0.0002460217,0.0003075153],"domain_scores_gemma":[0.9993592,0.00007679428,0.00004300093,0.0003397486,0.0001125739,0.00006870441],"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":[0.000004232762,0.00002230741,0.000003086569,0.00003491851,0.00002191121,0.000004129939,0.00008833875,0.3569024,0.6393026,0.002766034,0.0001759359,0.0006741367],"study_design_scores_gemma":[0.00007721466,0.0000201365,0.00003136959,0.00002136485,0.0000216978,0.000006852276,0.00005161148,0.5988688,0.3992411,0.001244766,0.0003125294,0.0001024805],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5741377,0.0001614092,0.4245499,0.0001586181,0.00004953657,0.0002299255,0.00002009919,0.0002108894,0.0004819752],"genre_scores_gemma":[0.9955707,0.00005104509,0.004147557,0.00005557056,0.0000309418,0.0000333166,0.00002082643,0.00003821631,0.00005178832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4214331,"threshold_uncertainty_score":0.4970766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02393188147621793,"score_gpt":0.261975450731144,"score_spread":0.2380435692549261,"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."}}