{"id":"W4306315481","doi":"10.1101/2022.10.13.22280980","title":"Identifying stable-against-mutations viral epitopes in SARS-CoV-2","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Windsor","funders":"European Commission; Natural Sciences and Engineering Research Council of Canada; Euskal Herriko Unibertsitatea; Basque Center for Applied Mathematics; European Regional Development Fund; Eusko Jaurlaritza","keywords":"Epitope; Biology; Mutation; Virology; Computational biology; Pandemic; Genetics; Antigen; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus disease 2019 (COVID-19); Disease; Gene; Medicine; Infectious disease (medical specialty)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004365379,0.0002783603,0.0002921276,0.0001574366,0.0001240389,0.0001093272,0.0005676309,0.0002213663,0.00002760464],"category_scores_gemma":[0.00008519341,0.0002923185,0.0001744176,0.0001242946,0.00003306429,0.000008606467,0.001492888,0.0005117041,0.00001322047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005040147,"about_ca_system_score_gemma":0.0001566831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009370584,"about_ca_topic_score_gemma":0.00006731736,"domain_scores_codex":[0.9984246,0.00009685746,0.0005346645,0.0004244242,0.0001926304,0.0003267523],"domain_scores_gemma":[0.9990186,0.00001085347,0.0002233467,0.0006697575,0.00004743008,0.00002999637],"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":[0.00007481455,0.000230763,0.03684164,0.0005272115,0.0002511982,0.00002351225,0.001323067,0.006581553,0.9483932,0.00031086,0.002082725,0.003359412],"study_design_scores_gemma":[0.002573519,0.0003045112,0.05677694,0.0002732909,0.0001453585,0.00002985849,0.002985631,0.008885691,0.8044765,0.003806917,0.1172585,0.002483244],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993679,0.00161055,0.0008231043,0.0001291319,0.0005769378,0.0003683783,0.00007407105,0.00002171618,0.002717135],"genre_scores_gemma":[0.9953055,0.0006351917,0.001639766,0.0002549678,0.000136554,0.0002085942,0.001394469,0.00004712388,0.0003777694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1439167,"threshold_uncertainty_score":0.9999529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04037569940140475,"score_gpt":0.2982197176279905,"score_spread":0.2578440182265858,"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."}}