{"id":"W2097961353","doi":"10.1128/jcm.02252-06","title":"Development of Multiple-Locus Variable-Number Tandem-Repeat Analysis for <i>Yersinia enterocolitica</i> subsp. <i>palearctica</i> and Its Application to Bioserogroup 4/O3 Subtyping","year":2007,"lang":"en","type":"article","venue":"Journal of Clinical Microbiology","topic":"Yersinia bacterium, plague, ectoparasites research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics","keywords":"Multiple Loci VNTR Analysis; Yersinia enterocolitica; Subtyping; Variable number tandem repeat; Biology; Genotyping; Genotype; Yersinia Infections; Tandem repeat; Minisatellite; Genetics; Locus (genetics); Ribotyping; Microbiology; Microsatellite; Escherichia coli; Enterobacteriaceae; Genome; Bacteria; Allele","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003507759,0.0002063348,0.0007785588,0.0002454882,0.00008583195,0.00001766144,0.0003467689,0.0004254152,0.00002204961],"category_scores_gemma":[0.001117641,0.0001852322,0.00032446,0.0004219141,0.0001533808,0.00001162821,0.0001862825,0.0002768081,0.000008071702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003953056,"about_ca_system_score_gemma":0.0002071151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003987592,"about_ca_topic_score_gemma":0.00008839226,"domain_scores_codex":[0.9969671,0.0001887701,0.001818091,0.0004107159,0.0001052567,0.000510006],"domain_scores_gemma":[0.9971617,0.0007747011,0.0006789762,0.0002721717,0.0007713181,0.0003411623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001574399,0.0002245656,0.1809679,0.00003964847,0.000700017,0.000002216225,0.00005462112,0.00001379051,0.8140581,0.00003462249,0.0000887342,0.002241402],"study_design_scores_gemma":[0.005614277,0.001964387,0.1258656,0.00008290225,0.0006732335,0.0005573652,0.0002211689,0.0001012362,0.7529896,0.00003258327,0.1113119,0.0005856972],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9441375,0.0001530503,0.05480931,0.0001544459,0.0001671302,0.0004651016,0.00003983825,0.000004304803,0.00006930426],"genre_scores_gemma":[0.9699848,0.00005538677,0.02915003,0.0003692215,0.0002668097,0.0000114226,0.00009173275,0.00002126516,0.00004933315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1112231,"threshold_uncertainty_score":0.7553549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0305333882186812,"score_gpt":0.370585017423899,"score_spread":0.3400516292052179,"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."}}