{"id":"W4296782706","doi":"10.1128/spectrum.02811-22","title":"Utilization of the Abbott SARS-CoV-2 IgG II Quant Assay To Identify High-Titer Anti-SARS-CoV-2 Neutralizing Plasma against Wild-Type and Variant SARS-CoV-2 Viruses","year":2022,"lang":"en","type":"article","venue":"Microbiology Spectrum","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Public Health Ontario; University of Toronto; Canadian Blood Services; Lunenfeld-Tanenbaum Research Institute; University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Innovates; Alberta Innovates - Health Solutions; Government of Canada","keywords":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Virology; Coronavirus disease 2019 (COVID-19); Titer; Food and drug administration; 2019-20 coronavirus outbreak; Convalescent plasma; Medicine; Pandemic; Virus; Pharmacology; Infectious disease (medical specialty); Internal medicine; Disease; Outbreak","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":[0.002199998,0.0009244159,0.0003263633,0.00105354,0.0004383495,0.0007860906,0.0006125827,0.0006971469,0.003399674],"category_scores_gemma":[0.002094198,0.0003836032,0.0003848193,0.0005335428,0.0004974804,0.0003281901,0.0005575904,0.000753575,0.00125696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005074401,"about_ca_system_score_gemma":0.0009733963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003863112,"about_ca_topic_score_gemma":0.006926542,"domain_scores_codex":[0.9946352,0.001584859,0.0003514585,0.0006095077,0.002440277,0.0003786998],"domain_scores_gemma":[0.9984414,0.0003708214,0.0002576523,0.0001618611,0.0006309554,0.0001373193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001083206,0.0007985124,0.06047341,0.0003066353,0.00008020395,0.0003735237,0.0004388413,0.0006456057,0.8694111,0.001482864,0.003974874,0.06093123],"study_design_scores_gemma":[0.0003773706,0.005307063,0.1231006,0.0001170791,0.000153412,0.007344861,0.0002368336,0.01315687,0.8303708,0.0005603465,0.01917056,0.0001042349],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8414111,0.002242658,0.1066856,0.0006630376,0.0004076,0.002471176,0.002202118,0.002804851,0.04111187],"genre_scores_gemma":[0.9151093,0.0005294849,0.07341023,0.0005454061,0.00008184076,0.0004524452,0.002198046,0.00008621088,0.007587013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003863112,"threshold_uncertainty_score":0.01163483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07058400745687958,"score_gpt":0.3565100178996395,"score_spread":0.2859260104427599,"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."}}