{"id":"W4324056392","doi":"10.3390/curroncol30030251","title":"The Potential of Adding Mammography to Handheld Ultrasound or Automated Breast Ultrasound to Reduce Unnecessary Biopsies in BI-RADS Ultrasound Category 4a: A Multicenter Hospital-Based Study in China","year":2023,"lang":"en","type":"article","venue":"Current Oncology","topic":"AI in cancer detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"GE Healthcare","keywords":"Medicine; Mammography; Biopsy; Ultrasound; Radiology; Logistic regression; Breast ultrasound; BI-RADS; Breast cancer; Cancer; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001640306,0.0004418784,0.000390979,0.000626435,0.0004573347,0.000650082,0.0006904191,0.0005233171,0.0006804626],"category_scores_gemma":[0.003927953,0.0003602877,0.0008086621,0.0008705785,0.0004983223,0.0007311588,0.0006832631,0.0004595395,0.00007433388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001157118,"about_ca_system_score_gemma":0.001936836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0200305,"about_ca_topic_score_gemma":0.02526484,"domain_scores_codex":[0.99887,0.0004441714,0.0001069392,0.0001935968,0.0001500036,0.0002352917],"domain_scores_gemma":[0.9982205,0.0002753799,0.0007123608,0.0001563208,0.0002144661,0.0004209969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001816362,0.0001143388,0.9960576,0.00002056908,0.00007535864,0.00006475921,0.000153248,0.00006533805,0.0002002153,0.0000176314,0.00007969895,0.002969526],"study_design_scores_gemma":[0.00003136917,0.0003469833,0.998449,0.000008212072,0.00009031285,0.00006478919,0.0002923525,0.0004735332,0.00007504677,0.0000199395,0.0001418903,0.000006549701],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996401,0.00009310118,0.0000462251,0.0000765257,0.00000295915,0.0000150042,0.00003863873,0.000001616071,0.00008578077],"genre_scores_gemma":[0.9996554,0.00005491236,0.00006958282,0.0000693239,0.000008647371,0.00001370129,0.00007576613,8.844054e-7,0.00005168328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0200305,"threshold_uncertainty_score":0.03982782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02767381926076122,"score_gpt":0.3432715318367426,"score_spread":0.3155977125759813,"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."}}