{"id":"W4282578445","doi":"10.3390/microorganisms10061199","title":"Phylogenomic Analysis of Salmonella enterica subsp. enterica Serovar Bovismorbificans from Clinical and Food Samples Using Whole Genome Wide Core Genes and kmer Binning Methods to Identify Two Distinct Polyphyletic Genome Pathotypes","year":2022,"lang":"en","type":"article","venue":"Microorganisms","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"Oak Ridge Institute for Science and Education; Joint Institute for Food Safety and Applied Nutrition, University of Maryland; U.S. Food and Drug Administration","keywords":"Polyphyly; Genome; Biology; Prophage; Salmonella enterica; Genetics; Serotype; Comparative genomics; Multiple Loci VNTR Analysis; Salmonella; Whole genome sequencing; Computational biology; Genomics; Gene; Phylogenetics; Clade; Bacteriophage; Virology; Tandem repeat; Escherichia coli","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001063294,0.0003448823,0.001057132,0.0001118595,0.0004524163,0.00007652086,0.000474702,0.0001030279,0.0004667413],"category_scores_gemma":[0.00009431415,0.0002017835,0.0002731072,0.0009357169,0.0003287921,0.00004834926,0.0008303021,0.0002218821,0.000005300369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006202125,"about_ca_system_score_gemma":0.00002181762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002079996,"about_ca_topic_score_gemma":0.000282379,"domain_scores_codex":[0.9964609,0.0009795249,0.000905327,0.0009851727,0.0001729232,0.0004962023],"domain_scores_gemma":[0.9981704,0.0008830496,0.0004138372,0.000224029,0.00005700973,0.0002517078],"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":[0.00004604488,0.00005710078,0.3640101,0.00000389244,0.0003149299,0.000007819448,0.0002713138,0.00003143642,0.6317979,0.000004076146,0.000003960057,0.003451457],"study_design_scores_gemma":[0.0002409475,0.0005261378,0.9889246,0.000005524431,0.0006979414,0.00003110832,0.0009226507,0.0001522946,0.004374438,0.0002748733,0.00347447,0.0003749939],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927499,0.003143473,0.001804105,0.0002640121,0.0001628468,0.0002662954,0.001562939,0.00004104423,0.00000543736],"genre_scores_gemma":[0.9867229,0.0001187991,0.01181941,0.000690372,0.000139734,0.0000148624,0.0004675786,0.00001001896,0.00001633422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6274235,"threshold_uncertainty_score":0.8228493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08816351048785823,"score_gpt":0.3466253236876605,"score_spread":0.2584618131998023,"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."}}