{"id":"W4312094723","doi":"10.1002/mp.16168","title":"Efficacy of ultrasound vector flow imaging in tracking omnidirectional pulsatile flow","year":2022,"lang":"en","type":"article","venue":"Medical Physics","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute for Aging; University of Waterloo","funders":"","keywords":"Pulsatile flow; Imaging phantom; Vector flow; Computational fluid dynamics; Flow (mathematics); Flow velocity; Flow visualization; Ultrasound; Acoustics; Materials science; Physics; Biomedical engineering; Mechanics; Optics; Computer science; Engineering; Artificial intelligence; Medicine","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":[0.002671298,0.0005602521,0.0003256807,0.0007627233,0.000162565,0.0007185863,0.000366963,0.0005562864,0.000439731],"category_scores_gemma":[0.008411025,0.0002284418,0.0001442479,0.0002503526,0.0005891897,0.0006808265,0.0004552881,0.0002381892,0.0001824278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001878177,"about_ca_system_score_gemma":0.0004326012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006883037,"about_ca_topic_score_gemma":0.0002950845,"domain_scores_codex":[0.9993302,0.0002847396,0.00004437554,0.0001687546,0.0001162286,0.00005580689],"domain_scores_gemma":[0.9966599,0.002258731,0.0003849491,0.0001811919,0.0004339304,0.00008140862],"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":[0.001908785,0.0001869227,0.01256203,0.000570999,0.00005984334,0.0001542402,0.0002984073,0.02038026,0.7910164,0.0004552253,0.0003349618,0.1720719],"study_design_scores_gemma":[0.00006739886,0.003276141,0.03190245,0.00009964288,0.0001626701,0.000961446,0.0001540326,0.1977723,0.7629242,0.0005175706,0.002065896,0.00009622087],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7856354,0.00254399,0.2088408,0.0001161191,0.00004978248,0.0001541327,0.0001355226,0.0007390049,0.00178515],"genre_scores_gemma":[0.9469555,0.0007953403,0.0514185,0.00007991292,0.00002283954,0.0000899363,0.0001118742,0.00008314274,0.0004429501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002671298,"threshold_uncertainty_score":0.01412737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01038724617824355,"score_gpt":0.2597573663726427,"score_spread":0.2493701201943992,"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."}}