{"id":"W4225524075","doi":"10.1371/journal.pone.0266829","title":"Using whole-genome sequence data to examine the epidemiology of antimicrobial resistance in Escherichia coli from wild meso-mammals and environmental sources on swine farms, conservation areas, and the Grand River watershed in southern Ontario, Canada","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Public Health Agency of Canada; University of Guelph","funders":"Ministère de l’Environnement, de la Protection de la nature et des Parcs; Ontario Ministry of Agriculture, Food and Rural Affairs; Public Health Agency; Public Health Agency of Canada; Ontario Agri-Food Innovation Alliance; University of Guelph","keywords":"Biology; Manure; Antibiotic resistance; Wildlife; Veterinary medicine; Escherichia coli; Multilocus sequence typing; Watershed; Ecology; Genotype; Genetics; Gene; Bacteria; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002912659,0.0002766011,0.0002011902,0.001068632,0.0006899508,0.000579996,0.0003993848,0.0002095985,0.000519726],"category_scores_gemma":[0.000957251,0.0001730788,0.0002425111,0.002344846,0.0003750385,0.0001692378,0.0003863657,0.0002237939,0.00008270929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003833097,"about_ca_system_score_gemma":0.005103136,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9380195,"about_ca_topic_score_gemma":0.976236,"domain_scores_codex":[0.9996137,0.00003646056,0.00002148198,0.0001011277,0.000121792,0.0001055199],"domain_scores_gemma":[0.9994174,0.00005445825,0.0001550935,0.00003030514,0.0002175647,0.0001252186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002800618,0.00001070186,0.9960218,0.0000128211,0.00003451432,0.00006866119,0.0003695164,0.00007581764,0.001434585,0.00001101338,0.00009608674,0.00183652],"study_design_scores_gemma":[0.000001409564,0.00001189808,0.9992231,0.000003494506,0.000007417819,0.00002983346,0.0003903836,0.00009132034,0.00005464111,0.00000225582,0.0001829315,0.000001293496],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984362,0.00008428418,0.0001079092,0.00001789264,9.899153e-7,0.00001886122,0.00111305,0.000002379403,0.0002185811],"genre_scores_gemma":[0.9967437,0.0001622154,0.0004270563,0.00003047204,0.000001582859,0.00001659678,0.002235114,0.000001838344,0.0003814204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06198049,"threshold_uncertainty_score":0.1246909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05376022571773689,"score_gpt":0.2263825428792717,"score_spread":0.1726223171615348,"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."}}