{"id":"W4211195376","doi":"10.1101/2022.01.27.478053","title":"Neutralization Of SARS-CoV-2 Variants By A Human Polyclonal Antibody Therapeutic (COVID-HIG, NP-028) With High Neutralizing Titers To SARS-CoV-2","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Emergent BioSolutions (Canada)","funders":"Biomedical Advanced Research and Development Authority; U.S. Department of Health and Human Services; Defense Health Agency; U.S. Department of Defense","keywords":"Virology; Neutralization; Neutralizing antibody; Polyclonal antibodies; Antibody; Medicine; Titer; Tolerability; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Monoclonal antibody; Immunology; Placebo; Clinical trial; Pharmacology; Disease; Adverse effect; Internal medicine; Infectious disease (medical specialty); Pathology","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":[0.0007293869,0.0005227234,0.0006662643,0.0002027438,0.0001552098,0.0004376213,0.0004305985,0.000557895,0.002559079],"category_scores_gemma":[0.0004399405,0.0002334397,0.0004363826,0.000215603,0.0002910552,0.0003051723,0.0001850233,0.00137002,0.0003369433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004210396,"about_ca_system_score_gemma":0.00047626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007957409,"about_ca_topic_score_gemma":0.001414989,"domain_scores_codex":[0.9997906,0.00006695474,0.00001490919,0.00003748338,0.00003211359,0.0000580021],"domain_scores_gemma":[0.9998416,0.0000350007,0.00003630051,0.00001359348,0.0000158318,0.00005756327],"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":[0.1895279,0.05123461,0.006378488,0.0006912861,0.0006017357,0.0003641482,0.0002188946,0.001521123,0.6405261,0.0003197512,0.003456407,0.1051594],"study_design_scores_gemma":[0.1541918,0.7266962,0.03068146,0.00006833627,0.0004612701,0.000782741,0.00008567162,0.003033454,0.07987034,0.0001166665,0.003985169,0.00002682242],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975291,0.0007046399,0.0002921019,0.00008463504,0.00005882968,0.0003396348,0.0002488011,0.00005207351,0.0006902251],"genre_scores_gemma":[0.9976573,0.0003567065,0.0004457977,0.0001453734,0.00004668546,0.0001725804,0.0005815979,0.000006001485,0.000587848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002559079,"threshold_uncertainty_score":0.008560956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04894733238961643,"score_gpt":0.3379982075470949,"score_spread":0.2890508751574785,"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."}}