{"id":"W3126247609","doi":"10.1016/j.vetmic.2021.109006","title":"Genomics accurately predicts antimicrobial resistance in Staphylococcus pseudintermedius collected as part of Vet-LIRN resistance monitoring","year":2021,"lang":"en","type":"article","venue":"Veterinary Microbiology","topic":"Antimicrobial Resistance in Staphylococcus","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Shared Health; Canadian Veterinary Medical Association; University of Prince Edward Island; Agriculture Food and Rural Development; University of Saskatchewan; University of Guelph","funders":"U.S. Food and Drug Administration; National Institutes of Health","keywords":"Staphylococcus pseudintermedius; Biology; Antibiotic resistance; Resistome; Broth microdilution; Antimicrobial; Staphylococcus aureus; rpoB; Salmonella enterica; Microbiology; Genotype; Salmonella; Drug resistance; Staphylococcus; Genetics; Gene; Antibiotics; Minimum inhibitory concentration; Bacteria","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004821598,0.0004902054,0.0004296213,0.0009168612,0.0004032255,0.001113971,0.0002685909,0.0008129397,0.001056172],"category_scores_gemma":[0.001406046,0.0002265372,0.0004119331,0.0007095801,0.0003411675,0.0003052127,0.0004581862,0.0004846019,0.0006862113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004831023,"about_ca_system_score_gemma":0.0004338438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005728353,"about_ca_topic_score_gemma":0.01199853,"domain_scores_codex":[0.9990747,0.000135658,0.00003754355,0.000325328,0.000298793,0.0001279013],"domain_scores_gemma":[0.9993027,0.0001816897,0.0001687017,0.00003729669,0.000231066,0.00007851526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003027599,0.0002025892,0.8467005,0.00008039964,0.0001099314,0.0002562154,0.0005099251,0.001015082,0.1371611,0.0001760815,0.001153215,0.01233225],"study_design_scores_gemma":[0.00001173318,0.0003734691,0.9567692,0.00005517965,0.0001198997,0.0009898396,0.001292694,0.006322838,0.02940515,0.0003020701,0.004335839,0.00002205769],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939529,0.0001924664,0.00111886,0.0001875998,0.00002059841,0.00002396847,0.003014189,0.00004019365,0.001449257],"genre_scores_gemma":[0.9919322,0.000151447,0.002068029,0.0003110278,0.00002021419,0.00001957765,0.004365438,0.00002538158,0.001106718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005728353,"threshold_uncertainty_score":0.01139003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04130630070654402,"score_gpt":0.3063150634485939,"score_spread":0.2650087627420499,"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."}}