{"id":"W269266826","doi":"10.1109/ultsym.2011.0142","title":"Improving CMUT receiving sensitivity using parametric amplification","year":2011,"lang":"en","type":"article","venue":"","topic":"Acoustic Wave Resonator Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Sensitivity (control systems); Parametric statistics; Acoustics; SIGNAL (programming language); Voltage; Capacitive micromachined ultrasonic transducers; Ultrasonic sensor; Materials science; Amplitude; Transducer; Computer science; Electronic engineering; Physics; Optics; Electrical engineering; Engineering; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005379723,0.0006167114,0.0004744991,0.0004711923,0.0003320001,0.0007466751,0.0008037102,0.0006780014,0.00160476],"category_scores_gemma":[0.002267645,0.0003494469,0.0002753571,0.0003307775,0.0004951445,0.001281424,0.0009201155,0.0006907896,0.0004482639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004156705,"about_ca_system_score_gemma":0.0002478685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002821825,"about_ca_topic_score_gemma":0.0004825704,"domain_scores_codex":[0.9992918,0.00009109645,0.00004176375,0.0001422918,0.0003263229,0.000106692],"domain_scores_gemma":[0.9983045,0.0008002624,0.0002952596,0.0001365913,0.0003839829,0.00007929326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008619468,0.00001251763,0.0003842816,0.00005915424,0.000007256835,0.000051889,0.00007088653,0.0007244333,0.9878313,0.0006056661,0.00007352007,0.01009281],"study_design_scores_gemma":[0.000007436357,0.0001832406,0.0006753629,0.000007179827,0.00001851634,0.0001938763,0.00001795093,0.006613084,0.9905797,0.00008856215,0.001598385,0.00001665761],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7582813,0.0015075,0.2323164,0.0004332494,0.0002285633,0.0001042831,0.00005784366,0.001533266,0.005537552],"genre_scores_gemma":[0.9349886,0.0003738858,0.06165571,0.0001371993,0.00009909465,0.0000280826,0.000050369,0.0001225483,0.002544486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00160476,"threshold_uncertainty_score":0.005368471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04651523972144668,"score_gpt":0.2204080233115439,"score_spread":0.1738927835900972,"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."}}