{"id":"W3036409630","doi":"10.2196/19371","title":"Structural Basis for Designing Multiepitope Vaccines Against COVID-19 Infection: In Silico Vaccine Design and Validation","year":2020,"lang":"en","type":"article","venue":"JMIR Bioinformatics and Biotechnology","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Epitope; Virology; In silico; CTL*; Biology; Coronavirus; Adjuvant; Immunogenicity; Proteome; Immune system; Computational biology; Immunology; Antigen; Medicine; CD8; Gene; Coronavirus disease 2019 (COVID-19); Bioinformatics; Genetics; Disease; Infectious disease (medical specialty)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003802391,0.0006686393,0.000491365,0.0002694414,0.0002012803,0.0004014581,0.0004678236,0.0004559605,0.001218427],"category_scores_gemma":[0.0005495415,0.0003338136,0.0005125268,0.0001825314,0.0001697822,0.0003213826,0.0001884726,0.0004982884,0.0004824152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004515992,"about_ca_system_score_gemma":0.000542016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004887145,"about_ca_topic_score_gemma":0.000639518,"domain_scores_codex":[0.9998943,0.00003178194,0.000007492829,0.00001741979,0.00003287899,0.00001617539],"domain_scores_gemma":[0.9998717,0.00005522968,0.00002252282,0.000009762806,0.00003027189,0.0000103984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003372165,0.0004147752,0.004609225,0.000611115,0.0001131192,0.0003911802,0.00008795462,0.4575154,0.5119284,0.004292989,0.0003947368,0.0193038],"study_design_scores_gemma":[0.0001050883,0.0008824301,0.0009859909,0.00004271293,0.000121781,0.0001753543,0.00006066438,0.7935463,0.1983179,0.001564004,0.00417744,0.00002042823],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8108811,0.001429874,0.181897,0.0003237039,0.00005242476,0.0003553839,0.0006090667,0.0003492986,0.004102167],"genre_scores_gemma":[0.8736418,0.001970608,0.121585,0.0001060548,0.00001568895,0.0002805987,0.001178504,0.00006645256,0.001155286],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001218427,"threshold_uncertainty_score":0.004076064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02859994386695318,"score_gpt":0.2676427998991772,"score_spread":0.239042856032224,"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."}}