{"id":"W4360591932","doi":"10.21037/hbsn-23-110","title":"Predicting early graft loss in pancreas transplantation using novel imaging techniques: are we there yet?","year":2023,"lang":"en","type":"letter","venue":"HepatoBiliary Surgery and Nutrition","topic":"Organ Transplantation Techniques and Outcomes","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Toronto General Hospital; University Health Network","funders":"","keywords":"Medicine; Transplantation; Pancreas transplantation; Pancreas; Surgery; Intensive care medicine; Radiology; Internal medicine; Kidney transplantation","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005042519,0.0004399855,0.000835165,0.0008868288,0.000129284,0.00005717925,0.00007119878,0.0006976274,0.0000269842],"category_scores_gemma":[0.00003299532,0.0004425882,0.0002605901,0.0004899098,0.0001028935,0.0003516432,0.00001435886,0.001228134,0.000003559677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00012981,"about_ca_system_score_gemma":0.000084722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009689166,"about_ca_topic_score_gemma":0.00007534852,"domain_scores_codex":[0.9976137,0.000140936,0.0007629289,0.0006256745,0.0003919815,0.0004647817],"domain_scores_gemma":[0.9985783,0.0006716956,0.0003021063,0.0002675685,0.00009625953,0.00008413548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003276722,0.0001553254,0.9598729,0.0139305,0.00005066173,0.004810226,0.0002919342,1.991075e-7,0.001012354,0.000004102394,0.01876557,0.0007785246],"study_design_scores_gemma":[0.007050239,0.0004872505,0.6716901,0.1556959,0.003194316,0.01135871,0.001255166,0.002044781,0.04988506,0.002851918,0.08987243,0.004614078],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8709689,0.002085472,0.001285329,0.1203964,0.0005008696,0.002042753,0.001287768,0.001375466,0.00005711339],"genre_scores_gemma":[0.6979567,0.1772496,0.004605856,0.103733,0.004466485,0.0008032719,0.01018788,0.0006793965,0.0003177962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2881828,"threshold_uncertainty_score":0.9998026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03642134231994969,"score_gpt":0.2727774867905406,"score_spread":0.2363561444705909,"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."}}