{"id":"W4411161874","doi":"10.1093/ve/veaf027","title":"Comprehensive analysis of SARS-CoV-2 Spike evolution: epitope classification and immune escape prediction","year":2025,"lang":"en","type":"article","venue":"Virus Evolution","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Research England; National Institute of Allergy and Infectious Diseases; Université Laval","keywords":"Immune escape; Spike (software development); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Epitope; Virology; Coronavirus disease 2019 (COVID-19); Immune system; Coronavirus; 2019-20 coronavirus outbreak; Immune recognition; Computational biology; Biology; Computer science; Antibody; Medicine; Immunology; Outbreak; Disease; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003344218,0.000195634,0.000529473,0.00136423,0.0001735868,0.0000246108,0.0001221763,0.0002307326,0.000007797124],"category_scores_gemma":[0.0001605853,0.0001924831,0.0002246423,0.002774821,0.0002578945,0.0001904933,0.00008623982,0.0002588414,0.00002719547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005847529,"about_ca_system_score_gemma":0.0002831345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001557027,"about_ca_topic_score_gemma":0.0001625506,"domain_scores_codex":[0.9980347,0.0001399097,0.0005931769,0.0004791603,0.0004675053,0.0002855947],"domain_scores_gemma":[0.9985127,0.0001058613,0.000186563,0.0005678736,0.0006005957,0.0000263648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004880231,0.0001980627,0.1145496,0.0001616795,0.0007290112,0.000002525667,0.00009069657,0.000009271528,0.8759402,0.003775261,0.0004541113,0.003601559],"study_design_scores_gemma":[0.001203176,0.0002016085,0.8013871,0.0001054773,0.001338382,0.000005899069,0.0002251359,0.04785055,0.1365601,0.0005972733,0.01040352,0.0001218126],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9751009,0.005554275,0.01530771,0.0003117886,0.0002562822,0.0005771416,0.00005465858,0.0001148927,0.002722318],"genre_scores_gemma":[0.9982778,0.00007756426,0.0001765056,0.001213128,0.00008648411,0.00005510711,0.00005302049,0.00001373705,0.0000466438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7393801,"threshold_uncertainty_score":0.7849233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05099962767178771,"score_gpt":0.3531902622259591,"score_spread":0.3021906345541714,"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."}}