{"id":"W4388284238","doi":"10.1126/sciadv.abp9185","title":"Phylogenetic identification of influenza virus candidates for seasonal vaccines","year":2023,"lang":"en","type":"article","venue":"Science Advances","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Phylogenetic tree; Hemagglutinin (influenza); Seasonal influenza; Neuraminidase; Identification (biology); Biology; Virology; Strain (injury); Selection (genetic algorithm); Pandemic; Virus; Computational biology; Evolutionary biology; Coronavirus disease 2019 (COVID-19); Genetics; Gene; Artificial intelligence; Computer science; Medicine; Ecology; Disease","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001140781,0.0004488514,0.0005238137,0.001234791,0.0004882251,0.0006324406,0.0002503779,0.000404084,0.002000677],"category_scores_gemma":[0.003496411,0.000186945,0.000467691,0.0007329915,0.0001300384,0.000561445,0.0003254951,0.00057203,0.0009055311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002585785,"about_ca_system_score_gemma":0.0004200345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001636878,"about_ca_topic_score_gemma":0.002756258,"domain_scores_codex":[0.9997104,0.0001119868,0.00001963048,0.00005563551,0.00004822439,0.00005408076],"domain_scores_gemma":[0.9988226,0.0004512596,0.0002798428,0.00008531526,0.0002445635,0.0001164046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001171068,0.0003476856,0.7497991,0.000223463,0.0002990419,0.0003574247,0.0003039995,0.03240043,0.08973036,0.001635718,0.004681255,0.1190505],"study_design_scores_gemma":[0.00009803483,0.001358967,0.449747,0.0001772029,0.000379015,0.00075812,0.0009184983,0.5051872,0.0252002,0.004557909,0.01155087,0.00006694614],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859349,0.001064127,0.009411548,0.000331606,0.00004178119,0.00004366284,0.001176578,0.0001506524,0.001845202],"genre_scores_gemma":[0.9838082,0.0002746614,0.01239084,0.00008556672,0.00002954327,0.0000190986,0.002942776,0.0000324998,0.0004167086],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002000677,"threshold_uncertainty_score":0.006692946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06498966921988135,"score_gpt":0.4281940849633885,"score_spread":0.3632044157435071,"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."}}