{"id":"W4212954711","doi":"10.3389/fvets.2022.838498","title":"Impact of a Regulation Restricting Critical Antimicrobial Usage on Prevalence of Antimicrobial Resistance in Escherichia coli Isolates From Fecal and Manure Pit Samples on Dairy Farms in Québec, Canada","year":2022,"lang":"en","type":"article","venue":"Frontiers in Veterinary Science","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Association des Médecins Vétérinaires du Québec; Fonds de Recherche du Québec – Nature et Technologies","funders":"Agriculture and Agri-Food Canada; Université de Montréal; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation","keywords":"Antibiotic resistance; Manure; Biology; Antimicrobial; Multiple drug resistance; Feces; Veterinary medicine; Herd; Salmonella; Biotechnology; Drug resistance; Microbiology; Antibiotics; Animal science; Medicine; Bacteria; Agronomy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039116,0.0001588332,0.0002563614,0.0002114245,0.0001013451,0.00001773739,0.000397891,0.00006599326,0.000009926883],"category_scores_gemma":[0.0003371713,0.0001691114,0.00003615567,0.0005141716,0.0005292749,0.00002616283,0.000214041,0.0001932974,4.696705e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003535183,"about_ca_system_score_gemma":0.0009186519,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06173193,"about_ca_topic_score_gemma":0.03197461,"domain_scores_codex":[0.9983336,0.0001808463,0.000395411,0.0005548974,0.0002203498,0.000314833],"domain_scores_gemma":[0.9993798,0.00007372577,0.0001565679,0.0003086823,0.00003330546,0.00004796165],"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":[0.001273646,0.00009679592,0.2958027,0.00007095587,0.000004051651,0.00002166206,0.0001500449,0.0006009091,0.7015012,0.000008740718,0.0003990444,0.00007027493],"study_design_scores_gemma":[0.0004847671,0.0007617351,0.9776574,0.0002485063,0.000003683939,0.000004971675,0.0001523015,0.0004103316,0.019972,0.00002999558,0.00009189541,0.0001824086],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988446,0.0002203252,0.0001002841,0.00009997678,0.0002894526,0.0001921524,0.0002023157,0.00000255305,0.00004833103],"genre_scores_gemma":[0.9947335,0.00006735732,0.005079715,0.00004378717,0.00001846742,0.000003549734,0.00001593457,0.00001069404,0.00002704484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6818547,"threshold_uncertainty_score":0.9856893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01123739509985032,"score_gpt":0.2565089300224708,"score_spread":0.2452715349226205,"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."}}