{"id":"W4377011664","doi":"10.1021/acsinfecdis.2c00610","title":"Synthetic Multicomponent Nanovaccines Based on the Molecular Co-assembly of β-Peptides Protect against Influenza A Virus","year":2023,"lang":"en","type":"article","venue":"ACS Infectious Diseases","topic":"Immunotherapy and Immune Responses","field":"Immunology and Microbiology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; PROTEO; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research","keywords":"Agonist; Epitope; TLR7; TLR9; Immune system; Antigen; Virus; Influenza A virus; Peptide; Receptor; Toll-like receptor; Biology; Chemistry; Virology; Innate immune system; Immunology; Biochemistry; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002949978,0.0002904774,0.0003508404,0.0003088318,0.0003685098,0.00002861755,0.0003188932,0.0001460754,0.0001314335],"category_scores_gemma":[0.0005566492,0.0001991235,0.0002502643,0.0004373757,0.0002653806,0.00006155063,0.00006256107,0.0002204851,0.0005878707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004560561,"about_ca_system_score_gemma":0.0001225573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001083847,"about_ca_topic_score_gemma":0.000004387552,"domain_scores_codex":[0.9981738,0.0006494986,0.0003825289,0.0003025531,0.00009075514,0.0004008769],"domain_scores_gemma":[0.9978305,0.001178741,0.0001988913,0.0006734411,0.00009632823,0.00002217218],"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":[0.0009241838,0.000540136,0.002925046,0.00005497081,0.0002757416,0.00001552597,0.0001114774,0.0007230117,0.9896166,0.0002983611,0.0007553173,0.003759589],"study_design_scores_gemma":[0.001886264,0.0005447587,0.01999525,0.0002118898,0.00008350397,0.00001029751,0.000123139,0.00008653018,0.967077,0.00009682492,0.009590837,0.0002937253],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955269,0.002384331,0.00004585708,0.0002056476,0.0002659348,0.0007361001,0.00009845619,0.0003407622,0.0003960759],"genre_scores_gemma":[0.9981883,0.0001321805,0.000002010265,0.001121066,0.00001277181,0.0003110493,0.00005419364,0.00004354763,0.0001348893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02253966,"threshold_uncertainty_score":0.812002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01420136107732175,"score_gpt":0.2638973681608295,"score_spread":0.2496960070835077,"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."}}