{"id":"W2609650626","doi":"10.1016/j.trre.2017.04.002","title":"Ex vivo machine perfusion for renal graft preservation","year":2017,"lang":"en","type":"review","venue":"Transplantation Reviews","topic":"Organ Transplantation Techniques and Outcomes","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"SickKids Foundation; Toronto General Hospital; Hospital for Sick Children; University of Toronto; University Health Network","funders":"","keywords":"Machine perfusion; Medicine; Perfusion; Cold storage; Dialysis; Economic shortage; Transplantation; Intensive care medicine; Ex vivo; Surgery; Internal medicine; In vivo; Liver 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":[0.0007953643,0.0006352536,0.002796574,0.0003017544,0.0002591089,0.00007650154,0.000340457,0.0004431582,0.000516949],"category_scores_gemma":[0.00007794702,0.0004529887,0.001344855,0.0001587411,0.00005419358,0.0002682966,0.0000102679,0.0003858309,0.0001488333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008408636,"about_ca_system_score_gemma":0.000196478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002836269,"about_ca_topic_score_gemma":0.0000371634,"domain_scores_codex":[0.9970282,0.0001733417,0.001542366,0.0006076992,0.0003265417,0.0003218205],"domain_scores_gemma":[0.9977161,0.0001702741,0.001038569,0.000781805,0.0001236862,0.0001695438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009979184,0.00005899955,0.00002662611,0.2051111,0.00008259233,0.0000262953,0.0001268778,7.186995e-8,0.00001153526,0.0001771397,0.002825608,0.7914533],"study_design_scores_gemma":[0.0009963643,0.0001805555,0.00004879319,0.03758479,0.007192171,0.0002685767,0.000001026369,0.00001309719,0.00007757249,0.00003058116,0.9531939,0.0004125374],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00000176639,0.9739092,0.0162044,0.0001411141,0.0002399463,0.007325983,0.0008392752,0.0001820503,0.001156268],"genre_scores_gemma":[0.000001180445,0.9769657,0.007518914,0.0002188714,0.0003179575,0.0008466413,0.006889896,0.0001120969,0.007128693],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9503683,"threshold_uncertainty_score":0.9997922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2046520884960665,"score_gpt":0.4510699418456824,"score_spread":0.2464178533496159,"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."}}