{"id":"W3092066114","doi":"10.1364/noma.2020.nom4c.5","title":"Simulation study of a piezoelectric micromachined ultrasonic transducer as terahertz differentiator","year":2020,"lang":"en","type":"article","venue":"OSA Advanced Photonics Congress (AP) 2020 (IPR, NP, NOMA, Networks, PVLED, PSC, SPPCom, SOF)","topic":"Photonic and Optical Devices","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; École de Technologie Supérieure","funders":"","keywords":"PMUT; Differentiator; Terahertz radiation; Capacitive micromachined ultrasonic transducers; Ultrasonic sensor; Piezoelectricity; Transducer; Acoustics; Materials science; SIGNAL (programming language); Pulse (music); Surface micromachining; Optoelectronics; Computer science; Optics; Physics; Bandwidth (computing); Telecommunications","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":[0.0001953582,0.0002973407,0.0003539844,0.0002789366,0.000457142,0.0004984071,0.0006758957,0.001447106,0.003270913],"category_scores_gemma":[0.0006884378,0.0003623722,0.0003852182,0.000347083,0.0005774414,0.0006579185,0.0003105403,0.0003760438,0.0002653664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006105074,"about_ca_system_score_gemma":0.0008108211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01169447,"about_ca_topic_score_gemma":0.005415423,"domain_scores_codex":[0.9998963,0.00002322686,0.000003078695,0.00001624109,0.00003622865,0.00002488008],"domain_scores_gemma":[0.9997498,0.0001197793,0.00003452759,0.00001640542,0.00005656472,0.00002280483],"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":[0.00004244271,0.00002106296,0.0007589924,0.00004634743,0.00001368074,0.0002373811,0.00006564458,0.986324,0.005270304,0.005554277,0.0002874866,0.001378362],"study_design_scores_gemma":[0.000009739186,0.00001390992,0.0001277012,0.000003724008,0.000004987728,0.00001750242,0.00001065907,0.9986748,0.0005736634,0.0002830321,0.0002766466,0.000003782862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.670422,0.001165461,0.2191027,0.001400471,0.0002248151,0.0001501997,0.0005848458,0.0004638842,0.1064856],"genre_scores_gemma":[0.9807506,0.0002998495,0.009702807,0.000078565,0.00001595506,0.00007844753,0.00007054722,0.00003472759,0.008968462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01169447,"threshold_uncertainty_score":0.02325279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008405200864062056,"score_gpt":0.2344051616176129,"score_spread":0.2259999607535509,"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."}}