{"id":"W4214864497","doi":"10.1186/s13550-018-0390-8","title":"Impact of time-of-flight PET on quantification accuracy and lesion detection in simultaneous 18F-choline PET/MRI for prostate cancer","year":2018,"lang":"en","type":"article","venue":"EJNMMI Research","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto General Hospital","funders":"","keywords":"Medicine; Prostate cancer; Nuclear medicine; Positron emission tomography; Magnetic resonance imaging; Correction for attenuation; Prostate; Lymph node; Cancer; Radiology; Metastasis; Pathology; Internal 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007902227,0.00008010771,0.0001961034,0.0002680368,0.00007784589,0.00001082972,0.00008918685,0.00003136842,0.00008916362],"category_scores_gemma":[0.001792703,0.00005980821,0.00004303663,0.000409162,0.0002540185,0.00003842481,0.00003667066,0.0002354834,0.00001192636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001027985,"about_ca_system_score_gemma":0.000144648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007262986,"about_ca_topic_score_gemma":0.00006509898,"domain_scores_codex":[0.9988641,0.00006703028,0.0002520594,0.0002499458,0.0003404754,0.000226442],"domain_scores_gemma":[0.9981363,0.0008109,0.00008790296,0.000306544,0.0005558964,0.0001023972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001664498,0.0004815521,0.003585459,0.000254851,0.00002315748,0.00001187042,0.0003366042,0.00002899835,0.9033157,0.00009399042,0.004323044,0.08588029],"study_design_scores_gemma":[0.002423667,0.004695444,0.0182496,0.0009398539,0.00003489178,0.00005057012,0.00008984025,0.2585565,0.7036821,0.0007013605,0.0103877,0.0001884937],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945403,0.00006289249,0.001280669,0.002474714,0.00001569043,0.001414763,0.00003431738,0.00002803994,0.000148572],"genre_scores_gemma":[0.9966974,0.000486053,0.00175873,0.00001741697,0.00009561456,0.0001816234,0.00003270934,0.00001681424,0.0007136598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2585275,"threshold_uncertainty_score":0.2438908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1070236027553759,"score_gpt":0.5085642620967907,"score_spread":0.4015406593414148,"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."}}