{"id":"W3146635033","doi":"10.1111/vox.13096","title":"Lessons learned in the collection of convalescent plasma during the COVID‐19 pandemic","year":2021,"lang":"en","type":"article","venue":"Vox Sanguinis","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Héma-Québec; Canadian Blood Services","funders":"Fogarty International Center","keywords":"Pandemic; Staffing; Preparedness; Medicine; Data collection; Coronavirus disease 2019 (COVID-19); Medical emergency; Nursing; Political science; Disease","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":[],"consensus_categories":[],"category_scores_codex":[0.1374819,0.001310407,0.001510759,0.001567018,0.006851943,0.01317989,0.00655809,0.01054488,0.003697055],"category_scores_gemma":[0.1884242,0.001136782,0.002010748,0.001416866,0.009967037,0.01464884,0.008827828,0.01927064,0.001552722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008876127,"about_ca_system_score_gemma":0.03568124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01975891,"about_ca_topic_score_gemma":0.02211663,"domain_scores_codex":[0.869149,0.09796079,0.007565294,0.004846967,0.01287608,0.007601781],"domain_scores_gemma":[0.7993339,0.1249855,0.009363732,0.00872457,0.03837481,0.0192174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00050023,0.000792647,0.03344549,0.00935941,0.0002882406,0.007385007,0.1851852,0.00287652,0.002612376,0.009188444,0.2197527,0.5286136],"study_design_scores_gemma":[0.0001613783,0.001746663,0.03020659,0.0214252,0.0001893501,0.005369157,0.4365678,0.00278402,0.003196116,0.0397461,0.4580298,0.00057793],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03481801,0.01542293,0.01135821,0.9214938,0.008552149,0.000563839,0.0002742443,0.0002402582,0.00727656],"genre_scores_gemma":[0.4928248,0.04515419,0.08971529,0.353431,0.009646105,0.001915108,0.0007563658,0.0005368121,0.006020221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1374819,"threshold_uncertainty_score":0.7270824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08289576132137998,"score_gpt":0.3125074062477539,"score_spread":0.2296116449263739,"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."}}