{"id":"W4200257959","doi":"10.1016/j.healun.2021.12.004","title":"Proteomics, brain death, and organ transplantation","year":2021,"lang":"en","type":"letter","venue":"The Journal of Heart and Lung Transplantation","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto General Hospital; University of Toronto; University Health Network","funders":"Government of Canada; Canadian Institutes of Health Research; Government of Ontario; University of Toronto; Ontario Research Foundation","keywords":"Medicine; Brain dead; Lung transplantation; Transplantation; Heart transplantation; Proteome; Internal medicine; Bioinformatics; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.004755904,0.0005966804,0.001525987,0.0009393172,0.003391485,0.003048697,0.001230457,0.02532159,0.004745961],"category_scores_gemma":[0.02143964,0.0003939132,0.0007452257,0.001075824,0.002688332,0.003075605,0.001286085,0.02217858,0.002276901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003278578,"about_ca_system_score_gemma":0.004315772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004785722,"about_ca_topic_score_gemma":0.009663976,"domain_scores_codex":[0.9976368,0.0009793796,0.0003029915,0.000203906,0.0006130704,0.0002638262],"domain_scores_gemma":[0.9891474,0.006375988,0.0007021122,0.0003162429,0.001562837,0.001895472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001826051,0.0001157567,0.005695278,0.00009215983,0.00004677243,0.002483506,0.0001170897,0.00005324643,0.0001078085,0.004226163,0.9591959,0.02768377],"study_design_scores_gemma":[0.0007556007,0.0003779223,0.02538923,0.001732489,0.0002469721,0.01410209,0.001843765,0.001514612,0.0005873909,0.05651022,0.8967331,0.0002065908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0007999574,0.00317793,0.0000553861,0.9814281,0.01245745,0.000005540662,0.00004710164,0.00001126357,0.002017324],"genre_scores_gemma":[0.01226247,0.005197564,0.0001699149,0.840048,0.1383957,0.00004016166,0.00005894854,0.00001349443,0.003813685],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02532159,"threshold_uncertainty_score":0.02515191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02296420288267742,"score_gpt":0.3015358088486152,"score_spread":0.2785716059659378,"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."}}