{"id":"W1975759059","doi":"10.1109/tuffc.2013.6644734","title":"Super-resolution imaging using multi- electrode CMUTs: theoretical design and simulation using point targets","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control","topic":"Ultrasonics and Acoustic Wave Propagation","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Academia Româna; Nanjing University of Science and Technology; Technische Universiteit Delft; CMC Microsystems","keywords":"Capacitive micromachined ultrasonic transducers; Acoustics; SIGNAL (programming language); Maximum a posteriori estimation; Materials science; Computer science; Optics; Physics; Transducer; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002964233,0.0003207594,0.0003779545,0.0002382521,0.0002125446,0.0004828191,0.0007284461,0.001205454,0.001153359],"category_scores_gemma":[0.0009602198,0.0003142099,0.0003957581,0.0003392315,0.0004264966,0.0006394343,0.0004134783,0.0003445198,0.0002150019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004311031,"about_ca_system_score_gemma":0.0004537284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002112579,"about_ca_topic_score_gemma":0.001339344,"domain_scores_codex":[0.9998829,0.00003273027,0.000003558627,0.00001594655,0.00005169446,0.00001306604],"domain_scores_gemma":[0.9996781,0.0001956588,0.0000404764,0.00002344436,0.0000480297,0.00001419937],"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":[0.0000286299,0.0000146092,0.0003117282,0.00005263856,0.000009991696,0.0001346911,0.00005155299,0.9771506,0.01066253,0.007013456,0.0001188883,0.004450728],"study_design_scores_gemma":[0.000001543074,0.000007223989,0.00003084368,0.000001077239,0.000001078646,0.00001580665,0.00000377486,0.9988534,0.0006564382,0.0003136927,0.0001131114,0.000001897189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09987105,0.0003436628,0.8923897,0.0002046988,0.00002003571,0.00005057098,0.00005455077,0.0002863525,0.006779379],"genre_scores_gemma":[0.7403087,0.0004765093,0.255731,0.00006162452,0.00001137704,0.0001879516,0.00004823044,0.00005876648,0.003115879],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002112579,"threshold_uncertainty_score":0.004200518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01280030233751636,"score_gpt":0.222106351309046,"score_spread":0.2093060489715296,"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."}}