{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000579145,0.0002440494,0.0002701573,0.0008616179,0.0004061607,0.0002927263,0.0002157442,0.000217206,0.0007982244],"category_scores_gemma":[0.0008195981,0.00008726934,0.0003073719,0.0005673957,0.0003217437,0.0001977158,0.0003350469,0.0002775934,0.0001181215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004189798,"about_ca_system_score_gemma":0.0002246058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00119145,"about_ca_topic_score_gemma":0.002214505,"domain_scores_codex":[0.999733,0.00006552901,0.00001499494,0.00008028851,0.0000607816,0.00004529319],"domain_scores_gemma":[0.99957,0.0001424425,0.0001343982,0.00002785803,0.00006161953,0.00006366838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004382589,0.00009545538,0.5602769,0.0001391314,0.0002102809,0.0006237546,0.0008814597,0.002859662,0.4011331,0.0003239268,0.000125157,0.03289285],"study_design_scores_gemma":[0.00001472024,0.0002496835,0.974804,0.00001885076,0.00005280986,0.0006778247,0.0002249372,0.01021886,0.01258414,0.0002188457,0.0009162747,0.00001896304],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990287,0.00005863941,0.000606891,0.000008093693,7.44493e-7,0.000006464891,0.00003900301,0.000005413046,0.0002461854],"genre_scores_gemma":[0.9988281,0.00002611756,0.0008839518,0.00001307869,0.000002194756,0.000009624427,0.0001591663,0.000003412857,0.00007435738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00119145,"threshold_uncertainty_score":0.003062844,"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."}}