{"id":"W4409016129","doi":"10.1016/j.csbj.2025.03.044","title":"Predicting pathogen evolution and immune evasion in the age of artificial intelligence","year":2025,"lang":"en","type":"review","venue":"Computational and Structural Biotechnology Journal","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Mila - Quebec Artificial Intelligence Institute; Montreal Heart Institute","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Evasion (ethics); Pathogen; Immune system; Biology; Computational biology; Immunology","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":[0.0004774131,0.0001740362,0.0006319606,0.000588049,0.0001661921,0.00003186932,0.0001924817,0.0003973601,0.000001561038],"category_scores_gemma":[0.0003143234,0.0001035292,0.0001225208,0.0004848119,0.0003557124,0.00003975557,0.0001263645,0.001125294,6.097869e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000768914,"about_ca_system_score_gemma":0.0003525823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001220117,"about_ca_topic_score_gemma":0.000004330007,"domain_scores_codex":[0.9985805,0.0001417918,0.0006348794,0.0002146749,0.0002546345,0.0001735414],"domain_scores_gemma":[0.9992008,0.000358223,0.0002256636,0.0001077831,0.00009434751,0.00001316216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003595492,0.0000119085,0.0004092193,0.00192184,0.00005507546,0.00009662964,0.00007064005,0.000003556009,0.0002333532,0.003830329,0.00000200094,0.9933295],"study_design_scores_gemma":[0.002286868,0.003060689,0.03137849,0.06749909,0.002506922,0.05906001,0.002642019,0.02910911,0.0009596817,0.6884093,0.1115156,0.001572166],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03009883,0.9665972,0.002381882,0.000372588,0.0001140435,0.0003805999,0.00001780422,0.00001400327,0.00002306765],"genre_scores_gemma":[0.0906114,0.9059972,0.002199935,0.0008253986,0.0002662145,0.00002040671,0.0000578295,0.00001832779,0.000003281721],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9917573,"threshold_uncertainty_score":0.4888903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05156466456248499,"score_gpt":0.3721172260345008,"score_spread":0.3205525614720158,"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."}}