{"id":"W2344847967","doi":"10.1111/ajt.13843","title":"Machine Perfusion of Donor Livers for Transplantation: A Proposal for Standardized Nomenclature and Reporting Guidelines","year":2016,"lang":"en","type":"review","venue":"American Journal of Transplantation","topic":"Organ Transplantation Techniques and Outcomes","field":"Medicine","cited_by":174,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto General Hospital","funders":"Wellcome Trust","keywords":"Medicine; Standardization; Nomenclature; Machine perfusion; Liver transplantation; Consistency (knowledge bases); Transplantation; Medical physics; Intensive care medicine; Computer science; Surgery; Taxonomy (biology); Artificial intelligence","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":[0.06564156,0.00175905,0.006253358,0.01206307,0.002159778,0.007507343,0.009850753,0.007745646,0.001408778],"category_scores_gemma":[0.05644258,0.001255789,0.006660257,0.01006834,0.00748617,0.008275158,0.005040071,0.01331931,0.001116518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007679598,"about_ca_system_score_gemma":0.04759948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01227678,"about_ca_topic_score_gemma":0.01105792,"domain_scores_codex":[0.9558871,0.01254391,0.01950399,0.0029481,0.00789527,0.001221615],"domain_scores_gemma":[0.943281,0.02182497,0.01161801,0.002706289,0.01924044,0.001329337],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002448912,0.0002995106,0.003746135,0.03146422,0.0006144398,0.0007436913,0.001440716,0.001758008,0.002669971,0.08362564,0.1274356,0.7459571],"study_design_scores_gemma":[0.0002076325,0.0003649837,0.006829641,0.09506855,0.001514618,0.002650162,0.001739331,0.001578929,0.002519463,0.03202529,0.8551391,0.0003623955],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002200388,0.8637062,0.03143241,0.08334232,0.009959863,0.001217649,0.001043425,0.0002828849,0.0068149],"genre_scores_gemma":[0.01282842,0.7847226,0.1603199,0.03178044,0.003873238,0.001900525,0.002445322,0.000121362,0.002008239],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9343584,"threshold_uncertainty_score":0.3471499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04962005960806797,"score_gpt":0.398875692178318,"score_spread":0.3492556325702501,"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."}}