{"id":"W2036635120","doi":"10.1016/j.diii.2012.06.004","title":"Tips and techniques in breast MRI","year":2012,"lang":"en","type":"review","venue":"Diagnostic and Interventional Imaging","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hôtel-Dieu de Montréal","funders":"","keywords":"Medicine; Subtraction; Magnetic resonance imaging; Breast MRI; Radiology; Biopsy; Breast cancer; Nuclear medicine; Mammography; Cancer","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003412653,0.0002975816,0.0009128845,0.0003378299,0.0000344342,0.0000462295,0.00007466282,0.0001103539,0.000402753],"category_scores_gemma":[0.0001293215,0.0002555262,0.0002499156,0.0001377428,0.0001405362,0.000161622,0.0001574558,0.0003829529,0.00002650079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00013356,"about_ca_system_score_gemma":0.00006502644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007912349,"about_ca_topic_score_gemma":0.000006291818,"domain_scores_codex":[0.998588,0.00007307332,0.0005404894,0.0003649387,0.0001683289,0.0002651248],"domain_scores_gemma":[0.9985921,0.0008737749,0.0001657361,0.000167952,0.00004987924,0.0001505383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003303421,0.0001632519,0.0288399,0.01266339,0.00006327782,0.00005710928,0.00001733814,2.871551e-9,6.880897e-8,0.0003901338,0.006137665,0.9516646],"study_design_scores_gemma":[0.000235646,0.00003292963,0.004743554,0.08087879,0.0008429972,0.002393685,0.00001477733,0.000004151711,0.000001179263,0.0001592018,0.9104577,0.0002354302],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001379907,0.996894,0.0001451175,0.001001515,0.0001567825,0.0005834607,0.00008949975,0.00004367619,0.001072168],"genre_scores_gemma":[0.0004567298,0.9976643,0.0006184555,0.0001753855,0.0003364622,0.0003829519,0.000167948,0.0000465231,0.000151214],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9514291,"threshold_uncertainty_score":0.9999897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04066231383628918,"score_gpt":0.3713853349077495,"score_spread":0.3307230210714603,"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."}}