{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009430358,0.0003136696,0.0001474191,0.00015678,0.00007077514,0.0001783764,0.0001287578,0.0002280337,0.0003850312],"category_scores_gemma":[0.0001261398,0.0001407298,0.0001465626,0.00008788189,0.0001499548,0.000220856,0.0001563737,0.0002896205,0.0001596377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001355541,"about_ca_system_score_gemma":0.00007817907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001120664,"about_ca_topic_score_gemma":0.000253357,"domain_scores_codex":[0.9999253,0.00001060845,0.000006891157,0.00002086812,0.0000195079,0.000016787],"domain_scores_gemma":[0.999922,0.00001258018,0.00003240833,0.000005839067,0.00001088192,0.00001623711],"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":[0.00002008687,0.00001078576,0.00004331466,0.00002092103,0.000003554185,0.00001175183,0.000004753056,0.00008863274,0.9988074,0.00004652036,0.00001307985,0.0009290754],"study_design_scores_gemma":[0.000006527929,0.0002198071,0.0007807918,0.00000336111,0.00001019505,0.00006925588,0.000006038073,0.0008383499,0.9966354,0.00002595805,0.001400355,0.000004053879],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900995,0.001327566,0.007316265,0.00004171414,0.0000467441,0.00006412393,0.0001130325,0.00008023744,0.0009108891],"genre_scores_gemma":[0.9898398,0.0007408945,0.007924871,0.00008889898,0.00001739247,0.00005598047,0.0002014491,0.00002565127,0.001105151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0003850312,"threshold_uncertainty_score":0.001288116,"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."}}