{"id":"W3151933045","doi":"10.1101/2021.03.23.21253520","title":"Optimizing SARS-CoV-2 Variant of Concern Screening: Experience from British Columbia, Canada, Early 2021","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; University of British Columbia; BC Centre for Disease Control","funders":"British Columbia Centre for Disease Control","keywords":"Concordance; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Turnaround time; Coronavirus disease 2019 (COVID-19); Whole genome sequencing; 2019-20 coronavirus outbreak; Public health; Medicine; Virology; Genome; Computational biology; Biology; Genetics; Engineering; Internal medicine; Operations management; Pathology; Gene; Infectious disease (medical specialty)","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":[0.003492631,0.0007403293,0.0004880785,0.0006586535,0.004162183,0.002272171,0.001094268,0.000878789,0.003151679],"category_scores_gemma":[0.005069651,0.000352914,0.0002353036,0.0014901,0.001116268,0.0005010907,0.001330224,0.001174151,0.0008466077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04267938,"about_ca_system_score_gemma":0.1026127,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9903638,"about_ca_topic_score_gemma":0.9944953,"domain_scores_codex":[0.997362,0.0004367945,0.00008095906,0.0002875138,0.0009092551,0.000923514],"domain_scores_gemma":[0.9932045,0.0003778425,0.0001488126,0.0001072115,0.004548548,0.001613055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002013837,0.001620197,0.4461119,0.0008160559,0.0001690863,0.003719095,0.01606138,0.005265262,0.01706725,0.002177848,0.1136907,0.3912874],"study_design_scores_gemma":[0.0004147255,0.001990357,0.7009081,0.001074759,0.0003236907,0.001505935,0.03282686,0.005839923,0.01189972,0.001191055,0.2417022,0.0003226718],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8901678,0.008884532,0.004895126,0.02014708,0.0003870418,0.001357087,0.007731381,0.0004468107,0.06598336],"genre_scores_gemma":[0.9480627,0.005027169,0.008217451,0.007132327,0.00006153795,0.0002051294,0.004045697,0.0002190269,0.02702915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04267938,"threshold_uncertainty_score":0.309662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06036674413451142,"score_gpt":0.3216003428997317,"score_spread":0.2612335987652202,"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."}}