{"id":"W3021146569","doi":"10.1007/978-981-15-1412-8_8","title":"BI-RADS Lexicon","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Women's College Hospital; University Health Network; Mount Sinai Hospital","funders":"","keywords":"Audit; Standardization; BI-RADS; Medical physics; Mammography; Medicine; Breast imaging; Quality assurance; Acronym; Radiology; Modality (human–computer interaction); Computer science; Artificial intelligence; Breast cancer; Pathology; Cancer; Accounting","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009361855,0.00135684,0.00102122,0.005922388,0.001077786,0.006328544,0.002040505,0.001887925,0.3418702],"category_scores_gemma":[0.003204128,0.0008463516,0.000616767,0.005406879,0.0006873934,0.004134714,0.002215854,0.002309687,0.3998654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001437088,"about_ca_system_score_gemma":0.002449412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003253475,"about_ca_topic_score_gemma":0.00754693,"domain_scores_codex":[0.999383,0.00007447656,0.00005361461,0.00008354688,0.000366626,0.00003874952],"domain_scores_gemma":[0.9984064,0.0004599541,0.0000728945,0.0001938222,0.0006829071,0.0001841567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001092072,0.00001101177,0.00003204644,0.0001947722,0.000002619559,0.00002561953,0.00003276947,0.0001336514,0.0003641835,0.01149303,0.8578887,0.1298109],"study_design_scores_gemma":[0.000001277525,0.000002183874,0.00005110528,0.00005864124,0.00000172994,0.0001049326,0.000009879302,0.0000802799,0.0001123806,0.002958813,0.9966151,0.000003703919],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0002988842,0.01147843,0.02669256,0.003892781,0.004167438,0.0001356724,0.009908106,0.00874645,0.9346798],"genre_scores_gemma":[0.001261444,0.007345747,0.01527258,0.001839734,0.001350772,0.0001246571,0.01266758,0.003919776,0.9562177],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3418702,"threshold_uncertainty_score":0.9387423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05593047362250966,"score_gpt":0.2903858586835984,"score_spread":0.2344553850610887,"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."}}