{"id":"W3217466224","doi":"10.1016/j.cpet.2021.09.006","title":"Artificial Intelligence in Lymphoma PET Imaging","year":2021,"lang":"en","type":"article","venue":"PET Clinics","topic":"Lymphoma Diagnosis and Treatment","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"NIH Clinical Center; National Institutes of Health","keywords":"Medicine; Lymphoma; Risk stratification; Pet imaging; Segmentation; Artificial intelligence; Positron emission tomography; Radiology; Pathology; Computer science; 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":[0.0002112246,0.0001204558,0.000275846,0.00006085698,0.0000354765,0.0000292286,0.00005571539,0.00002268008,0.0002983481],"category_scores_gemma":[0.0003907781,0.0001099215,0.0001199107,0.0002357663,0.00004236317,0.00005714251,0.00006050706,0.00006879687,0.0003205606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001544764,"about_ca_system_score_gemma":0.0003174154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005200858,"about_ca_topic_score_gemma":0.0001331215,"domain_scores_codex":[0.9987872,0.00004040619,0.0004419149,0.0003135521,0.0001809344,0.0002359978],"domain_scores_gemma":[0.9991722,0.0002545108,0.00005984902,0.0003229502,0.00008615932,0.0001043097],"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":[0.00009270441,0.002284179,0.39486,0.00004228058,0.00004975253,0.01706698,0.0002550606,0.00001455307,0.00007572146,0.00547166,0.0004318968,0.5793552],"study_design_scores_gemma":[0.004050081,0.0004612522,0.8670018,0.0008611337,0.0004811578,0.005803787,0.003008506,0.02925938,0.02331114,0.02081458,0.04406375,0.0008834672],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882763,0.000992119,0.0001216924,0.004095905,0.0004829517,0.0001416703,0.00001148228,0.00004806027,0.005829802],"genre_scores_gemma":[0.9948257,0.0008178845,0.002510209,0.001352547,0.0001691425,0.00002235602,0.00004661012,0.0000159462,0.000239558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5784718,"threshold_uncertainty_score":0.4482468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03816215394911705,"score_gpt":0.3492320684004292,"score_spread":0.3110699144513122,"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."}}