{"id":"W3052624576","doi":"10.1155/2020/9089768","title":"Adaptive Evolution of Feline Coronavirus Genes Based on Selection Analysis","year":2020,"lang":"en","type":"article","venue":"BioMed Research International","topic":"Animal Virus Infections Studies","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Key Research and Development Program of China; Department of Education of Liaoning Province; Ministry of Science and Technology of the People's Republic of China","keywords":"Phylogenetic tree; Biology; Clade; Gene; CATS; Coronavirus; Feline infectious peritonitis; Genetics; Phylogenetics; Selection (genetic algorithm); Viral evolution; Genome; Virology; Coronavirus disease 2019 (COVID-19)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003549164,0.00007142096,0.0001154661,0.000135405,0.0001858383,0.00002061916,0.0002005974,0.00004977661,0.0008350394],"category_scores_gemma":[0.0002639091,0.00003177444,0.0001144094,0.002009794,0.0001379864,0.00005675476,0.0000742803,0.000131562,0.00006430973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001821587,"about_ca_system_score_gemma":0.00002105887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008775648,"about_ca_topic_score_gemma":0.0005499095,"domain_scores_codex":[0.9986056,0.0001451773,0.0001704403,0.0002400924,0.0006748674,0.0001638032],"domain_scores_gemma":[0.9989913,0.0002579085,0.00006279902,0.00002458649,0.0005927366,0.00007070199],"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":[0.001287454,0.0005324503,0.1442729,0.000006962693,0.000743881,0.000003418523,0.00007094892,0.002431103,0.7893357,0.0032589,0.003861225,0.05419507],"study_design_scores_gemma":[0.0002998215,0.002219482,0.762229,0.00001353181,0.00005172024,6.614833e-7,0.0004476809,0.1871231,0.01731038,0.0002397428,0.02989793,0.0001670232],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9834043,0.000155104,0.002605986,0.008625232,0.0002503696,0.0003007708,0.0003790864,0.00008871977,0.004190482],"genre_scores_gemma":[0.9990162,0.00002242778,0.0002381484,0.00006886689,0.0004606118,0.00002323926,0.00006284908,6.758407e-7,0.0001069585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7720253,"threshold_uncertainty_score":0.9143095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2180248429624923,"score_gpt":0.382200979937779,"score_spread":0.1641761369752867,"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."}}