{"id":"W2135456932","doi":"10.1002/mrm.22819","title":"Extended graphical model for analysis of dynamic contrast‐enhanced MRI","year":2011,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Robarts Clinical Trials","funders":"","keywords":"Partial volume; Positron emission tomography; Dynamic contrast-enhanced MRI; Graphical model; Nuclear medicine; Mathematics; Magnetic resonance imaging; Statistics; Radiology; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.001968371,0.001633995,0.001298999,0.001756674,0.0004367122,0.001663206,0.002353368,0.001890031,0.005092817],"category_scores_gemma":[0.007855343,0.0007605155,0.00235211,0.001397327,0.001109149,0.001965966,0.001248118,0.002112752,0.001741455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001522869,"about_ca_system_score_gemma":0.001266952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01476531,"about_ca_topic_score_gemma":0.008632654,"domain_scores_codex":[0.9986689,0.0004497982,0.00007345996,0.0003422233,0.0003131754,0.0001523902],"domain_scores_gemma":[0.9967486,0.002103952,0.0003914579,0.0001777452,0.0004855288,0.00009281754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008596518,0.00003444461,0.00109324,0.0001127839,0.00008793853,0.000254955,0.0000886634,0.9168052,0.003419386,0.05905989,0.001314323,0.01764323],"study_design_scores_gemma":[0.000003828982,0.00001056481,0.0001157917,0.00000548445,0.00001204094,0.00002775063,0.00000423955,0.9914142,0.0001860917,0.007556504,0.000653511,0.00000982874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005145669,0.0003715839,0.9924759,0.0001643565,0.0000420344,0.00003763056,0.0002602461,0.0004597217,0.00104277],"genre_scores_gemma":[0.6754352,0.002713978,0.2969962,0.0006168904,0.0002979375,0.0009764301,0.002474887,0.0007510008,0.01973744],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01476531,"threshold_uncertainty_score":0.02935869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03616885381330788,"score_gpt":0.3252763221668303,"score_spread":0.2891074683535224,"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."}}