{"id":"W3026628563","doi":"10.1111/bjh.16736","title":"Triage tool for the rationing of blood for massively bleeding patients during a severe national blood shortage: guidance from the National Blood Transfusion Committee","year":2020,"lang":"en","type":"article","venue":"British Journal of Haematology","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Economic shortage; Triage; Rationing; Medicine; Blood transfusion; Pandemic; Intensive care medicine; Medical emergency; Transfusion medicine; Blood supply; Business; Health care; Coronavirus disease 2019 (COVID-19); Emergency medicine; Surgery; Economics","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0009879671,0.0001586937,0.0004043149,0.00009756618,0.0007051842,0.0002875932,0.0004645881,0.0001023638,0.0001767028],"category_scores_gemma":[0.002778809,0.0001309005,0.000269143,0.0002751282,0.00007949911,0.001171693,0.00005448124,0.0002970625,0.000001866436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007972208,"about_ca_system_score_gemma":0.0001022784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005530623,"about_ca_topic_score_gemma":0.0000917455,"domain_scores_codex":[0.9978417,0.00005848073,0.000986057,0.0002252892,0.0006877325,0.0002007848],"domain_scores_gemma":[0.9952394,0.001624713,0.001144252,0.00006134237,0.001909657,0.00002059995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01274475,0.01240921,0.5431782,0.005993859,0.0213892,0.001687847,0.006041458,0.008046323,0.05953662,0.2031569,0.09393638,0.03187929],"study_design_scores_gemma":[0.2021046,0.001333123,0.5843484,0.00427865,0.02302422,0.01324549,0.00568905,0.02232611,0.02825681,0.03827774,0.0737694,0.003346376],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9805794,0.0009057039,0.003319512,0.01341138,0.0003903457,0.0008152915,0.0001823575,0.00002252592,0.0003734739],"genre_scores_gemma":[0.9949018,0.0001608208,0.001689246,0.00208491,0.001014022,0.000057077,0.00004772074,0.00002612064,0.00001824337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1893598,"threshold_uncertainty_score":0.5423778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02688763157647418,"score_gpt":0.2467420349619851,"score_spread":0.219854403385511,"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."}}