{"id":"W4307336708","doi":"10.1111/trf.17151","title":"A <scp>data‐informed</scp> system to manage scarce blood product allocation in a randomized controlled trial of convalescent plasma","year":2022,"lang":"en","type":"article","venue":"Transfusion","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Kingston Health Sciences Centre; University of Toronto; Canadian Blood Services; Sunnybrook Health Science Centre; University of British Columbia; Health Sciences Centre; Queen's University; Centre Hospitalier Universitaire Sainte-Justine; McMaster University; Vancouver Coastal Health; Centre Hospitalier de l’Université de Montréal; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canadian Blood Services","keywords":"Economic shortage; Operations management; Randomized controlled trial; Randomization; Product (mathematics); Distribution (mathematics); Resource allocation; Time allocation; Business; Scarcity; Medicine; Operations research; Computer science; Economics; Engineering; Surgery","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04192184,0.001202745,0.001669096,0.0008082927,0.0006337593,0.001514085,0.001669414,0.001998376,0.0157423],"category_scores_gemma":[0.05468914,0.0009226727,0.001401179,0.0009682541,0.001039216,0.001437265,0.00140398,0.00233024,0.001025424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00239621,"about_ca_system_score_gemma":0.008869112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002415254,"about_ca_topic_score_gemma":0.004041034,"domain_scores_codex":[0.9551026,0.03950395,0.001837676,0.001708159,0.001214719,0.000632935],"domain_scores_gemma":[0.9520115,0.0329633,0.00778635,0.002892133,0.002134347,0.002212432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"not_applicable","study_design_scores_codex":[0.6866876,0.01054446,0.005489507,0.00555174,0.004876277,0.0002070589,0.0005473996,0.02692699,0.002578055,0.005697646,0.0414044,0.2094887],"study_design_scores_gemma":[0.8325987,0.03089017,0.004397691,0.0005148855,0.001583543,0.00005098127,0.0000743407,0.1094159,0.002220942,0.0037625,0.01438276,0.0001075944],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.3530491,0.002649205,0.2329252,0.01493656,0.003627643,0.3478882,0.01535865,0.01152774,0.01803787],"genre_scores_gemma":[0.5416525,0.0004592039,0.1721294,0.004042083,0.0005296909,0.2758463,0.00159127,0.000274519,0.003475072],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04192184,"threshold_uncertainty_score":0.2217065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01829941754963985,"score_gpt":0.2438138880840968,"score_spread":0.225514470534457,"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."}}