{"id":"W4387920579","doi":"10.4329/wjr.v15.i10.293","title":"Two-point Dixon and six-point Dixon magnetic resonance techniques in the detection, quantification and grading of hepatic steatosis","year":2023,"lang":"en","type":"article","venue":"World Journal of Radiology","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Northern Alberta Clinical Trials and Research Centre; University of Alberta; Alberta Health Services","keywords":"Steatosis; Medicine; Grading (engineering); Fatty liver; Magnetic resonance imaging; Correlation; Receiver operating characteristic; Nuclear medicine; Radiology; Internal medicine; Gastroenterology; Mathematics; Disease","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":[],"consensus_categories":[],"category_scores_codex":[0.0006431267,0.00009256947,0.0003127416,0.0003651355,0.00004562241,0.000009264787,0.00005437878,0.00003056544,0.000007693346],"category_scores_gemma":[0.00009380816,0.00005954194,0.0000567128,0.0002881181,0.0001075459,0.00005751306,0.00001692158,0.0001264433,7.580834e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004982111,"about_ca_system_score_gemma":0.00002214211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005661895,"about_ca_topic_score_gemma":0.0001784601,"domain_scores_codex":[0.9990439,0.0001936509,0.0003929897,0.0001280127,0.0001162733,0.0001251024],"domain_scores_gemma":[0.9991875,0.0003663125,0.0002008764,0.0001329851,0.00005712868,0.00005513999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003984342,0.0002668134,0.8578079,0.0001441232,0.0000823775,0.0002057254,0.001309212,0.000004552579,0.01164448,0.0008966555,0.0007189513,0.1265207],"study_design_scores_gemma":[0.001269987,0.001111739,0.9839041,0.0003303525,0.0002193983,0.0006840369,0.0004792358,0.0002211392,0.0101398,0.0009048273,0.0006683997,0.00006697218],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850411,0.01232697,0.00004598829,0.002155631,0.00006721364,0.0002721203,0.000002924957,0.00001090038,0.0000771242],"genre_scores_gemma":[0.9917445,0.007754588,0.0002687135,0.0001139248,0.00006223629,0.00002699969,0.000002217148,0.000007995142,0.00001878122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1264538,"threshold_uncertainty_score":0.242805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01690853901621508,"score_gpt":0.2767589832614987,"score_spread":0.2598504442452836,"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."}}