{"id":"W2512971597","doi":"10.5772/62449","title":"Ex-Vivo Lung Perfusion: From Bench to Bedside","year":2016,"lang":"en","type":"book-chapter","venue":"InTech eBooks","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian VIGOUR Centre; Alberta Biodiversity Monitoring Institute; Canadian Natural Resources; University of Alberta","funders":"Faculty of Medicine and Dentistry, University of Alberta; University of Alberta","keywords":"Lung transplantation; Medicine; Bench to bedside; Transplantation; Intensive care medicine; Ex vivo; Lung; Perfusion; Surgery; Cardiology; In vivo; Internal medicine; Medical physics; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001736878,0.0004547369,0.0007505307,0.0002663418,0.00007107708,0.00002622849,0.000222964,0.0005158799,0.004982398],"category_scores_gemma":[0.00004445805,0.0003283844,0.0003253032,0.00001154857,0.00008956686,0.00002439756,0.00008392277,0.0005071848,0.0006225841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001344004,"about_ca_system_score_gemma":0.0001554649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008775944,"about_ca_topic_score_gemma":0.0001007789,"domain_scores_codex":[0.9981181,0.00002188861,0.0005107956,0.0005836139,0.0004687713,0.0002968388],"domain_scores_gemma":[0.9984138,0.0003181947,0.0001310023,0.0006745508,0.0001590474,0.0003034235],"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":[0.001396596,0.0000464752,0.001464875,0.0005621245,0.001061014,0.002474996,0.004010808,7.225909e-8,0.3821379,0.06470025,0.0116788,0.530466],"study_design_scores_gemma":[0.001547802,0.0003285479,0.0005494109,0.004973576,0.0008207554,0.000158648,0.00004529885,0.000001314499,0.1577385,0.02692607,0.8060984,0.0008116237],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001447386,0.0004504063,0.01798596,0.00129777,0.001007572,0.0008116271,0.0003335804,0.0002252584,0.9764404],"genre_scores_gemma":[0.0114712,0.00009397408,0.01658873,0.00268594,0.001258626,0.00003120656,0.00005004967,0.000132461,0.9676878],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7944196,"threshold_uncertainty_score":0.9999168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02881222499268355,"score_gpt":0.3087522615384529,"score_spread":0.2799400365457694,"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."}}