{"id":"W2159595075","doi":"10.1109/tmi.2009.2016561","title":"<i>B</i>-Mode Ultrasound Image Simulation in Deformable 3-D Medium","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Imaging phantom; Pixel; Interpolation (computer graphics); Computer vision; Computer science; Artificial intelligence; Voxel; Deformation (meteorology); Image (mathematics); Optics; Physics","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":[0.0005177117,0.0003889068,0.0003271343,0.0004255246,0.0002972026,0.0007050991,0.0008117213,0.0009279484,0.002645291],"category_scores_gemma":[0.001373231,0.0003706602,0.0006059518,0.0002964078,0.0005004311,0.0005626812,0.0007005822,0.0005280053,0.0005827264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004767783,"about_ca_system_score_gemma":0.0004727271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001882455,"about_ca_topic_score_gemma":0.001442453,"domain_scores_codex":[0.999827,0.00003924686,0.00001192759,0.00002216731,0.00008816307,0.0000114963],"domain_scores_gemma":[0.9995856,0.0002448038,0.00003336595,0.00006129369,0.00005583399,0.00001914487],"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":[0.0001747675,0.0000361754,0.000523093,0.0001262334,0.00003104579,0.0001962772,0.0002600325,0.8289529,0.055735,0.022789,0.001081851,0.09009366],"study_design_scores_gemma":[0.00001038251,0.00001808532,0.00006047645,0.00000469287,0.00000241689,0.00004017964,0.00000949419,0.9877394,0.008652126,0.001797409,0.001657989,0.000007337801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004155634,0.00001817834,0.9945415,0.00003056995,0.000008627537,0.00002554057,0.00001741242,0.0004743126,0.0007282898],"genre_scores_gemma":[0.1121204,0.00008674645,0.8859027,0.00004467531,0.000008166458,0.0001475976,0.00007805695,0.0002262149,0.001385435],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002645291,"threshold_uncertainty_score":0.008849382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009900441601966601,"score_gpt":0.3110087914725959,"score_spread":0.3011083498706292,"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."}}