{"id":"W3205122988","doi":"10.5772/intechopen.98309","title":"Tracking <i>Salmonella</i> Enteritidis in the Genomics Era: Clade Definition Using a SNP-PCR Assay and Implications for Population Structure","year":2021,"lang":"en","type":"book-chapter","venue":"IntechOpen eBooks","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Institut National de Santé Publique du Québec; Centre for Interdisciplinary Research in Rehabilitation; University of Guelph; Canadian Food Inspection Agency","funders":"Ministry of Agriculture, Food and Rural Affairs; Ontario Ministry of Agriculture, Food and Rural Affairs; Government of Canada; Canadian Food Inspection Agency","keywords":"Subtyping; Biology; Salmonella enterica; Salmonella; Clade; Computational biology; Salmonella enteritidis; Phylogenetic tree; Genetics; Serotype; Genome; Population; Typing; Genomics; Gene; Virology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002212658,0.0003773923,0.0004270158,0.0009503822,0.0002356352,0.001155352,0.0005184038,0.0005006075,0.0003998093],"category_scores_gemma":[0.00229697,0.0002221118,0.0003009421,0.0009642164,0.0003680998,0.0006369629,0.0006127447,0.0008690469,0.0003711956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002752166,"about_ca_system_score_gemma":0.0001853717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001117295,"about_ca_topic_score_gemma":0.001505207,"domain_scores_codex":[0.998955,0.0003428724,0.00004399857,0.0004229296,0.0001785475,0.00005670028],"domain_scores_gemma":[0.998755,0.0004797167,0.0003329767,0.00007997013,0.0002639607,0.00008838525],"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":[0.0004347371,0.000152536,0.3436815,0.0003962611,0.0001650029,0.0001756399,0.002406664,0.004238279,0.5416158,0.002818773,0.0009509854,0.1029639],"study_design_scores_gemma":[0.0000197051,0.0007858793,0.8141186,0.0003043536,0.0002824185,0.000916332,0.002671586,0.07832599,0.08712379,0.005600859,0.009735135,0.0001153898],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.906772,0.002611563,0.08480056,0.0003908677,0.00004031185,0.0000623676,0.001562399,0.0002711883,0.003488824],"genre_scores_gemma":[0.9108813,0.0009012634,0.08557852,0.0003032115,0.00002550276,0.0000546689,0.001478456,0.00006465203,0.000712345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002212658,"threshold_uncertainty_score":0.01170182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09896457925848187,"score_gpt":0.2853502120042044,"score_spread":0.1863856327457225,"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."}}