{"id":"W2141770816","doi":"10.1109/iembs.2007.4352750","title":"Simulation of Ultrasound Radio-Frequency Signals in Deformed Tissue for Validation of 2D Motion Estimation with Sub-Sample Accuracy","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Interpolation (computer graphics); Sampling (signal processing); Estimator; Computer science; Motion estimation; Deformation (meteorology); SIGNAL (programming language); Joint (building); Frequency domain; Acoustics; Algorithm; Computer vision; Mathematics; Motion (physics); Physics; Filter (signal processing); Statistics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005607624,0.0001380919,0.0002863953,0.0003698934,0.00003971149,0.00002215813,0.00006686732,0.00008586316,0.00001753189],"category_scores_gemma":[0.002397693,0.0001201048,0.00004419093,0.0005102413,0.0001009834,0.0004843359,0.000004720362,0.00009551915,7.858581e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005645224,"about_ca_system_score_gemma":0.00008347045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009335531,"about_ca_topic_score_gemma":0.000006928605,"domain_scores_codex":[0.9988401,0.000005179855,0.0004734806,0.0002121663,0.0002537103,0.000215395],"domain_scores_gemma":[0.9977792,0.000754689,0.0003743037,0.00008216854,0.0009470104,0.00006262988],"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":[0.0004857478,0.0001858675,0.2419169,0.0007656589,0.00003135544,1.61833e-7,0.003069497,0.002250404,0.7281615,0.0004940415,0.000007494064,0.02263135],"study_design_scores_gemma":[0.002505084,0.001105215,0.1311911,0.0008503482,0.000174363,0.00001912562,0.00117604,0.02819869,0.8283834,0.006089727,0.00006277781,0.0002440702],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5731475,0.00001744752,0.4261519,0.00003479767,0.00001753882,0.0004781769,0.000007054205,0.00002181765,0.0001237963],"genre_scores_gemma":[0.9611792,0.00001204944,0.03858866,0.00001286271,0.00002947278,0.00002626396,0.0001280658,0.00001550973,0.000007939754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3880317,"threshold_uncertainty_score":0.4897733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02546726765225784,"score_gpt":0.3103494614661182,"score_spread":0.2848821938138604,"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."}}