{"id":"W4298002307","doi":"10.3390/v14102126","title":"Lessons Learned from the COVID-19 Pandemic and How Blood Operators Can Prepare for the Next Pandemic","year":2022,"lang":"en","type":"review","venue":"Viruses","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Canadian Blood Services; University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Pandemic; Middle East respiratory syndrome coronavirus; Outbreak; Coronavirus disease 2019 (COVID-19); Middle East respiratory syndrome; Public health; Coronavirus; Medicine; Virology; Infectious disease (medical specialty); Disease; Pathology","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":[0.001647986,0.0007077789,0.0009386324,0.002278602,0.0003878675,0.001954388,0.0007506715,0.001962067,0.004725913],"category_scores_gemma":[0.002830419,0.0002665584,0.000841456,0.002012079,0.0008172219,0.00314887,0.0008088062,0.003043869,0.001394716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00131507,"about_ca_system_score_gemma":0.003151709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00323913,"about_ca_topic_score_gemma":0.005214876,"domain_scores_codex":[0.9995135,0.0001458426,0.00005570466,0.00007164048,0.0001591898,0.00005405134],"domain_scores_gemma":[0.9985586,0.0008197304,0.000122136,0.0000297858,0.0003636999,0.0001060734],"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":[0.0000843684,0.00008411373,0.0002185951,0.02754494,0.0001032042,0.0001955296,0.0003146503,0.000487263,0.0005749215,0.01666511,0.08698925,0.866738],"study_design_scores_gemma":[0.00001194238,0.0000678622,0.0005539262,0.01301503,0.00008040941,0.0004968133,0.0002191183,0.00007327423,0.0001187495,0.005772131,0.9795747,0.00001590633],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00007637258,0.9957768,0.00006638916,0.002572309,0.0003230534,0.000003207409,0.0000169445,0.000005195866,0.0011598],"genre_scores_gemma":[0.0007740076,0.9971936,0.0001469895,0.001213745,0.0002212704,0.000005644278,0.00002121399,0.000001511048,0.0004220434],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004725913,"threshold_uncertainty_score":0.01580971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4813863944065468,"score_gpt":0.4770473003162098,"score_spread":0.004339094090337003,"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."}}