{"id":"W2335169398","doi":"10.1097/tp.0000000000000891","title":"Developing Statistical Models to Assess Transplant Outcomes Using National Registries","year":2015,"lang":"en","type":"review","venue":"Transplantation","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Work & Health; University of Toronto","funders":"U.S. Public Health Service; Health Resources and Services Administration","keywords":"Organ procurement; Cohort; Medicine; Organ transplantation; Transplantation; Risk assessment; Medical physics; Surgery; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001026203,0.0004957695,0.001607632,0.0002365519,0.0001118758,0.00009365009,0.0002786226,0.0002848064,0.00004391795],"category_scores_gemma":[0.0003928907,0.0003980309,0.0001548416,0.0003005163,0.00006129678,0.0001442479,0.00001443512,0.0003078007,0.00003090629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003655301,"about_ca_system_score_gemma":0.001186305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004521538,"about_ca_topic_score_gemma":0.00002322591,"domain_scores_codex":[0.9967948,0.0004192891,0.001047151,0.0004852346,0.0008896342,0.0003638506],"domain_scores_gemma":[0.9956853,0.003319234,0.0002619578,0.0001971523,0.0003294803,0.0002068484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002542451,0.00003445142,0.000002956892,0.02066195,0.0001274108,0.00004616654,0.0004363481,0.0000375305,3.834122e-7,0.8273174,0.0001612385,0.1511488],"study_design_scores_gemma":[0.0006577486,0.00009153153,0.00001742451,0.02045004,0.002994673,0.0003004252,0.0000523779,0.002565784,0.000004985568,0.9068969,0.06444584,0.001522312],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000007688972,0.08847303,0.9063856,0.00002261807,0.0002176902,0.0007110014,0.003312576,0.00008677562,0.0007830291],"genre_scores_gemma":[0.0000148875,0.442017,0.5572692,0.00004060183,0.00005504961,0.00007592332,0.0004402697,0.00005272653,0.00003432003],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.353544,"threshold_uncertainty_score":0.9998472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7513622453270469,"score_gpt":0.5505413125442806,"score_spread":0.2008209327827662,"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."}}