{"id":"W4414759640","doi":"10.3390/tomography11100111","title":"Quantitative Volumetric Analysis Using 3D Ultrasound Tomography for Breast Mass Characterization","year":2025,"lang":"en","type":"article","venue":"Tomography","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre; University of Toronto; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"National Cancer Institute; National Institutes of Health; Sunnybrook Research Institute","keywords":"Breast cancer; Mammography; Magnetic resonance imaging; Breast imaging; Ultrasound; Breast ultrasound; BI-RADS; Medical imaging; Ultrasonography","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003409443,0.000345356,0.0006843476,0.007426854,0.0003249804,0.0001301319,0.0001629687,0.0001497956,0.00008660296],"category_scores_gemma":[0.0001191779,0.0003349173,0.001240563,0.01922183,0.000240612,0.0002460755,0.0000166369,0.0002142445,0.000004588249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004272331,"about_ca_system_score_gemma":0.00007464251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007832935,"about_ca_topic_score_gemma":0.000009314735,"domain_scores_codex":[0.997949,0.00007349872,0.000499377,0.000621405,0.0003220464,0.0005346591],"domain_scores_gemma":[0.9982767,0.0003586277,0.0002040238,0.0004928756,0.0004956736,0.0001721084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004626399,0.0003166995,0.8235041,0.0002103135,0.00498469,0.00000169845,0.0002041738,0.00005065318,0.1658753,0.0004859045,0.00014319,0.003760633],"study_design_scores_gemma":[0.001809899,0.0003544035,0.9761015,0.000197499,0.008740901,0.00003771841,0.0004262702,0.005318194,0.00120138,0.000454402,0.004832145,0.0005256454],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5487384,0.0005858059,0.4480702,0.0001599155,0.0003160314,0.0006177029,0.0004364966,0.0002204822,0.00085507],"genre_scores_gemma":[0.9286548,0.00007118233,0.06948604,0.0005185318,0.00009658503,0.00007476794,0.0007819809,0.00004064958,0.0002754056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3799165,"threshold_uncertainty_score":0.9999103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01248683523491448,"score_gpt":0.28503013932063,"score_spread":0.2725433040857155,"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."}}