{"id":"W2035031006","doi":"10.1128/aem.00704-08","title":"Diversity and Distribution of Commensal Fecal<i>Escherichia coli</i>Bacteria in Beef Cattle Administered Selected Subtherapeutic Antimicrobials in a Feedlot Setting","year":2008,"lang":"en","type":"article","venue":"Applied and Environmental Microbiology","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; Agriculture and Agri-Food Canada","funders":"Bundesinstitut für Risikobewertung; Agriculture and Agri-Food Canada; University of Alberta; University of Guelph","keywords":"Feedlot; Escherichia coli; Feces; Beef cattle; Biology; Bacteria; Microbiology; Distribution (mathematics); Antimicrobial; Biotechnology; Veterinary medicine; Animal science; Medicine; Genetics; Mathematics","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":[0.0002367485,0.0001970677,0.0003359216,0.0004847448,0.0002667788,0.0004349838,0.0001322973,0.0003504354,0.0004315058],"category_scores_gemma":[0.0004505017,0.0001476609,0.0001461161,0.0002730817,0.0002621213,0.0002015423,0.000140079,0.0002573406,0.00009741054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003645192,"about_ca_system_score_gemma":0.0001926161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003846722,"about_ca_topic_score_gemma":0.005232864,"domain_scores_codex":[0.9997038,0.00005184594,0.00002071952,0.00007858918,0.00006153317,0.00008347469],"domain_scores_gemma":[0.9995642,0.00007055262,0.0001369125,0.00001459227,0.00007716662,0.0001364376],"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":[0.003478609,0.0005809593,0.3538353,0.00008777231,0.00006494392,0.0002802377,0.0005615834,0.0002138248,0.6315797,0.00002392886,0.00008637726,0.009206697],"study_design_scores_gemma":[0.00001018596,0.003456138,0.9761739,0.00000609852,0.00004021597,0.000247687,0.000340259,0.0001810968,0.01934516,0.000008032172,0.0001817531,0.000009405475],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997934,0.00005331376,0.00002879099,0.000004952023,8.504406e-7,0.000002532773,0.00004894487,0.000001429006,0.00006595247],"genre_scores_gemma":[0.9993283,0.00009272237,0.000120722,0.00001873882,0.000004668725,0.000005544015,0.0001783227,0.000001232243,0.0002497602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003846722,"threshold_uncertainty_score":0.007648706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007904623904495566,"score_gpt":0.1925288663235265,"score_spread":0.184624242419031,"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."}}