{"id":"W4415368699","doi":"10.1109/ius62464.2025.11201536","title":"MBFormer: A Transformer model for 3D Time-Series Data Processing to Improve Bound Bubble Detection in Nondestructive Ultrasound Molecular Imaging","year":2025,"lang":"","type":"article","venue":"","topic":"Flow Measurement and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health","keywords":"Microbubbles; Transformer; Encoder; Ultrasound; Pattern recognition (psychology); Nondestructive testing; Iterative reconstruction; Correlation coefficient","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006781952,0.0005613379,0.0006266622,0.0007244931,0.0003185165,0.0005261264,0.0005426964,0.0001651022,0.00005109669],"category_scores_gemma":[0.000148555,0.0006134022,0.0001778039,0.001361674,0.00007317946,0.002233447,0.00006880098,0.0003154307,0.00001429879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000473816,"about_ca_system_score_gemma":0.0003156085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001991077,"about_ca_topic_score_gemma":0.001146023,"domain_scores_codex":[0.9969205,0.00002603265,0.0008189129,0.0009942739,0.0003636943,0.0008765559],"domain_scores_gemma":[0.9987948,0.0000546563,0.00007322519,0.0006954704,0.0002457483,0.000136076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002477075,0.00007410504,0.0001189473,0.0008202969,0.0003265995,0.000002193486,0.0009619385,0.1106916,0.7379938,0.000108531,0.00007240668,0.1485818],"study_design_scores_gemma":[0.000973453,0.00004308387,0.00002749681,0.0002606589,0.0004991627,0.000002449983,0.0005659713,0.8569564,0.1384347,0.001232065,0.0004317484,0.0005727879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02437251,0.0009622846,0.9673465,0.0002629828,0.0002355322,0.0013458,0.0001233159,0.0001397605,0.005211319],"genre_scores_gemma":[0.9448245,0.00006184995,0.05259503,0.0001581628,0.00006638085,0.0002162562,0.00009706557,0.00009147017,0.001889318],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9204519,"threshold_uncertainty_score":0.9996318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01031310149192043,"score_gpt":0.2430903534118711,"score_spread":0.2327772519199506,"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."}}