{"id":"W2800439744","doi":"10.3389/fmicb.2018.00836","title":"Salmonella enterica Prophage Sequence Profiles Reflect Genome Diversity and Can Be Used for High Discrimination Subtyping","year":2018,"lang":"en","type":"article","venue":"Frontiers in Microbiology","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; Public Health Agency of Canada; Institut National de Santé Publique du Québec; Health Canada; Université de Montréal; Université Laval; McGill University; Canadian Food Inspection Agency","funders":"Canadian Food Inspection Agency; Public Health Agency of Canada; Genome Canada","keywords":"Prophage; Subtyping; Biology; Salmonella enterica; Salmonella; Genome; Genetics; Serotype; Typing; Microbiology; Gene; Bacteriophage; Bacteria; Escherichia coli","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003288977,0.0001616096,0.0003259978,0.00003431423,0.0004233628,0.0000129204,0.0002479693,0.0001901844,0.00002761784],"category_scores_gemma":[0.00008897833,0.00007771783,0.00004550006,0.0001494379,0.0004010551,0.00005847714,0.0002943884,0.0000954803,0.000001811515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008384466,"about_ca_system_score_gemma":0.000009460605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004683923,"about_ca_topic_score_gemma":0.0008852567,"domain_scores_codex":[0.998651,0.0002090904,0.0002236843,0.000478266,0.00002854308,0.0004094528],"domain_scores_gemma":[0.9995782,0.0001172195,0.0001214667,0.00006246366,0.00005557146,0.00006508252],"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":[0.0000971016,0.00002362304,0.2162695,0.00001077752,0.00001389242,0.000002168564,0.0005176294,1.876464e-7,0.7804459,0.00005134996,0.0006162784,0.001951586],"study_design_scores_gemma":[0.001201872,0.002521061,0.9082832,0.00005081295,0.00006950968,0.0000837176,0.001442379,0.0001007335,0.06245876,0.005416895,0.01749559,0.0008754868],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967521,0.0002236268,0.0002654316,0.001592871,0.0004587433,0.0004537122,0.0001981507,0.0000349211,0.00002041793],"genre_scores_gemma":[0.9966165,0.00008041454,0.001873655,0.0007225834,0.0001861321,0.00002932847,0.0003647538,0.000001685782,0.0001249335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7179872,"threshold_uncertainty_score":0.3256207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04196211225866381,"score_gpt":0.2524054734833197,"score_spread":0.2104433612246559,"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."}}