{"id":"W3155069380","doi":"10.1039/d1sc01203g","title":"Prediction and mitigation of mutation threats to COVID-19 vaccines and antibody therapies","year":2021,"lang":"en","type":"article","venue":"Chemical Science","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Nvidia; National Institute of General Medical Sciences; George Mason University; Nuclear Safety and Security Commission; Bristol-Myers Squibb; National Aeronautics and Space Administration; National Institutes of Health; National Science Foundation; Michigan Economic Development Corporation; National Institute of Allergy and Infectious Diseases; Pfizer","keywords":"Antibody; Mutation; Mutant; Biology; Virology; Genetics; Immune system; Computational biology; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002341539,0.00004902363,0.00009492152,0.00006717169,0.00006516953,0.00002719789,0.00004699894,0.00003324469,0.000005014387],"category_scores_gemma":[0.000848387,0.00003923458,0.0000120149,0.0005208479,0.0002563391,0.0001162521,0.00005585995,0.00004912374,0.000001224183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000462803,"about_ca_system_score_gemma":0.0002467287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002334165,"about_ca_topic_score_gemma":0.000002746826,"domain_scores_codex":[0.9992371,0.00000970806,0.0001018327,0.0002429909,0.0002900108,0.000118356],"domain_scores_gemma":[0.9995419,0.00008211747,0.0000209701,0.000102654,0.000165916,0.00008647449],"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":[0.00003344458,0.00002225714,0.0838936,0.00005611199,0.000003131259,0.000005718474,0.0005888526,1.234373e-7,0.9091194,0.00009992015,0.00001733689,0.006160118],"study_design_scores_gemma":[0.000399695,0.00006574696,0.057467,0.00003336159,0.000008379656,0.00005723365,0.0002395735,0.0004087158,0.9398032,0.001019427,0.0004612224,0.00003643263],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965905,0.0004826607,0.0007455625,0.001739359,0.00002387489,0.0001292307,0.000003142028,0.00001855668,0.0002670979],"genre_scores_gemma":[0.9942328,0.00001822909,0.0004738458,0.005220597,0.00003477391,0.000006226616,0.000003311395,0.000002681511,0.000007493703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03068383,"threshold_uncertainty_score":0.159994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04396807327905102,"score_gpt":0.3892556198755521,"score_spread":0.3452875465965011,"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."}}