{"id":"W4285819971","doi":"10.1109/tuffc.2022.3189345","title":"Ultrafast Orthogonal Row–Column Electronic Scanning (uFORCES) With Bias-Switchable Top-Orthogonal-to-Bottom Electrode 2-D Arrays","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of Alberta","funders":"National Eye Institute; National Institutes of Health; Mitacs; Canadian Institutes of Health Research; National Heart, Lung, and Blood Institute; Alberta Innovates; Natural Sciences and Engineering Research Council of Canada","keywords":"Column (typography); Row and column spaces; Ultrashort pulse; Imaging phantom; Matrix (chemical analysis); Notation; Optics; Computer science; Algorithm; Materials science; Row; Physics; Mathematics; Telecommunications; Arithmetic","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":[0.0002024701,0.0002821661,0.000155753,0.0001376384,0.00008774397,0.0002886108,0.0004869628,0.0003600953,0.001159599],"category_scores_gemma":[0.0003949631,0.0001780607,0.0001158396,0.0001726907,0.0003171914,0.0004192898,0.0004150344,0.0002359958,0.0002269183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002744372,"about_ca_system_score_gemma":0.0002101236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004524243,"about_ca_topic_score_gemma":0.001376867,"domain_scores_codex":[0.9998711,0.00001793174,0.000005820224,0.00002649798,0.00005840394,0.00002019177],"domain_scores_gemma":[0.9997666,0.00009294777,0.00006487816,0.00003109746,0.00002975541,0.00001468254],"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":[0.00006478169,0.00001964097,0.000356298,0.00008047924,0.000008658351,0.000103672,0.00005554675,0.003048193,0.9706541,0.003184025,0.0004085733,0.02201607],"study_design_scores_gemma":[0.00002036246,0.0001867756,0.0008338386,0.000007456376,0.000007562956,0.0002421333,0.00003001259,0.03518006,0.955603,0.0003978634,0.007466901,0.00002405181],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6321743,0.00141668,0.3539008,0.0003368932,0.0001319845,0.0001272345,0.0002083676,0.001296038,0.01040773],"genre_scores_gemma":[0.7224567,0.0005775137,0.2710744,0.0002425395,0.00002543021,0.00009014926,0.0001500571,0.00006923886,0.00531397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001159599,"threshold_uncertainty_score":0.003879249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008325595224242392,"score_gpt":0.2163397090001861,"score_spread":0.2080141137759438,"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."}}