{"id":"W4386637980","doi":"10.1016/j.ajt.2023.09.002","title":"Augmenting the United States transplant registry with external mortality data: A moving target ripe for further improvement","year":2023,"lang":"en","type":"article","venue":"American Journal of Transplantation","topic":"Organ Donation and Transplantation","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nortel (Canada)","funders":"Health Resources and Services Administration; U.S. Social Security Administration; Centers for Medicare and Medicaid Services; U.S. Department of Health and Human Services","keywords":"Organ procurement; Medicine; Transplantation; United Network for Organ Sharing; Organ transplantation; Kidney transplantation; Intensive care medicine; Emergency medicine; Surgery","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2050101,0.003449717,0.008026578,0.01069727,0.001980948,0.01665537,0.01498828,0.007068195,0.01212416],"category_scores_gemma":[0.334361,0.00229831,0.006257451,0.01563897,0.003462209,0.04098467,0.01516185,0.01566372,0.006963156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006360987,"about_ca_system_score_gemma":0.04966997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05988191,"about_ca_topic_score_gemma":0.05560632,"domain_scores_codex":[0.9192932,0.04472812,0.01348018,0.005941127,0.0129748,0.003582688],"domain_scores_gemma":[0.4185719,0.2311928,0.04023838,0.09689493,0.1792865,0.03381542],"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":[0.001429002,0.001451644,0.3277662,0.01023273,0.003321567,0.0002660544,0.002253608,0.004640263,0.001898145,0.0158619,0.2503211,0.3805579],"study_design_scores_gemma":[0.00101761,0.002078503,0.3754224,0.02890588,0.003288246,0.0008999383,0.009923,0.01997358,0.00266527,0.03601455,0.5189121,0.000898924],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06049202,0.05058961,0.0990932,0.6808055,0.01742962,0.004330602,0.06599135,0.00723304,0.01403505],"genre_scores_gemma":[0.190433,0.03394089,0.4585364,0.1215943,0.01370229,0.004554043,0.1711019,0.001839399,0.004297817],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2050101,"threshold_uncertainty_score":0.9803641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02768171923403777,"score_gpt":0.3058041487658235,"score_spread":0.2781224295317857,"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."}}