{"id":"W2026846414","doi":"10.1002/jmri.22872","title":"Water‐silicone separated volumetric MR acquisition for rapid assessment of breast implants","year":2012,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Breast Implant and Reconstruction","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Silicone; Medicine; Biomedical engineering; Breast MRI; Nuclear medicine; Radiology; Materials science; Breast cancer; Mammography; Internal medicine; Composite material","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":[],"consensus_categories":[],"category_scores_codex":[0.0007470385,0.0001379339,0.0004307959,0.0003820693,0.0000578465,0.00001814798,0.00007974489,0.00005524389,0.0002120485],"category_scores_gemma":[0.00001462285,0.00009486847,0.0001628333,0.0001998761,0.00007124792,0.0003238119,0.00001895103,0.0001825516,0.000004251741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000829468,"about_ca_system_score_gemma":0.00009402526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009790127,"about_ca_topic_score_gemma":2.333937e-7,"domain_scores_codex":[0.9984982,0.00005126867,0.0006593434,0.0001037594,0.0003209222,0.0003665115],"domain_scores_gemma":[0.9988676,0.00006847629,0.000373251,0.0001224755,0.0004044544,0.0001637564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004962246,0.0002017677,0.1820423,0.0001213974,0.0000305007,0.00001570551,0.0001065883,0.000002963038,0.08796871,0.00001270378,0.001140983,0.7278602],"study_design_scores_gemma":[0.004107372,0.0004224688,0.8430002,0.0003949343,0.0002525146,0.1338675,0.0001405939,0.002365142,0.01314725,0.00003730586,0.002122904,0.0001417726],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987704,0.009330905,0.001074093,0.0004493546,0.0008405782,0.000255114,0.00003706563,0.00001038854,0.0002984681],"genre_scores_gemma":[0.9942393,0.0001616607,0.004687979,0.00004725289,0.0006665103,0.000004666871,0.00001588909,0.00001734296,0.0001594233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7277184,"threshold_uncertainty_score":0.3868624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01287220787041334,"score_gpt":0.2903837538229962,"score_spread":0.2775115459525829,"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."}}