{"id":"W3037461879","doi":"10.1371/journal.pcbi.1007892","title":"Implications of localized charge for human influenza A H1N1 hemagglutinin evolution: Insights from deep mutational scans","year":2020,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fogarty International Center; Science and Technology Directorate; Natural Sciences and Engineering Research Council of Canada; Bill and Melinda Gates Foundation; National Science Foundation; National Institutes of Health; James S. McDonnell Foundation; Medical Research Council; U.S. Department of Homeland Security","keywords":"Hemagglutinin (influenza); Avidity; Immune escape; Charge (physics); Immune system; Viral evolution; Biophysics; Surface charge; Influenza A virus; Biology; Evolutionary biology; Static electricity; Chemical physics; Chemistry; Antibody; Nanotechnology; Virus; Genetics; Physics; Gene; Materials science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001010842,0.0003376061,0.0003929898,0.001169049,0.0004104778,0.0007005695,0.0003629895,0.0004572921,0.0006354558],"category_scores_gemma":[0.003114609,0.0001855351,0.0004284904,0.0007248044,0.0006439142,0.0007174392,0.0007713164,0.0003830615,0.0001159344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004253415,"about_ca_system_score_gemma":0.0002217326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001700268,"about_ca_topic_score_gemma":0.002497438,"domain_scores_codex":[0.9997925,0.00008383266,0.00001095577,0.00005459737,0.00002913154,0.00002904571],"domain_scores_gemma":[0.9993204,0.0003400236,0.0001255132,0.00005477212,0.00005233475,0.00010694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001028863,0.0001855566,0.635763,0.0002422785,0.0004858163,0.001367613,0.001829909,0.1602085,0.1491219,0.005586338,0.0004386128,0.04374161],"study_design_scores_gemma":[0.00004749755,0.0003088642,0.4976245,0.000040516,0.000143396,0.0008685795,0.00115606,0.4742868,0.007385035,0.01693029,0.001133457,0.00007495181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969777,0.0001150292,0.002449647,0.00006459262,0.000001210179,0.000004115826,0.00009848081,0.00001568534,0.0002736082],"genre_scores_gemma":[0.9989985,0.00006197091,0.0007686027,0.00001932777,0.00000203462,0.000003241895,0.00009694783,0.00000806654,0.00004137999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001700268,"threshold_uncertainty_score":0.005345881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1436535908808776,"score_gpt":0.397483108531006,"score_spread":0.2538295176501285,"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."}}