{"id":"W2729843280","doi":"10.1093/gbe/evx115","title":"Genomic Epidemiology of NDM-1-Encoding Plasmids in Latin American Clinical Isolates Reveals Insights into the Evolution of Multidrug Resistance","year":2017,"lang":"en","type":"article","venue":"Genome Biology and Evolution","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut National Du Cancer; University of Technology Sydney; Universidad El Bosque; Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)","keywords":"Plasmid; Klebsiella pneumoniae; Acinetobacter baumannii; Biology; Microbiology; Antibiotic resistance; Molecular epidemiology; Enterobacteriaceae; Multiple drug resistance; Acinetobacter; Escherichia coli; Antibiotics; Genetics; Gene; Bacteria; Genotype; Pseudomonas aeruginosa","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001140427,0.0002417029,0.0001801309,0.000706751,0.0002590419,0.0004126476,0.0001457072,0.0002244202,0.000759995],"category_scores_gemma":[0.000532329,0.0001008014,0.0001655699,0.0006364099,0.0002091701,0.00009685442,0.0002489207,0.0002422589,0.0001039356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005294209,"about_ca_system_score_gemma":0.0003143456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02272485,"about_ca_topic_score_gemma":0.02100792,"domain_scores_codex":[0.999859,0.00001695585,0.00001282889,0.00005617387,0.00002316171,0.00003184952],"domain_scores_gemma":[0.9997624,0.00003498601,0.0001150129,0.00001941187,0.00003957552,0.00002871037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007377408,0.00006123332,0.8650755,0.0001666449,0.00007000437,0.0008776392,0.001159073,0.0001936584,0.1136437,0.0001201244,0.0002544992,0.01764025],"study_design_scores_gemma":[0.000007927692,0.00005262628,0.9927443,0.00002287123,0.00004522591,0.001136443,0.0006109022,0.0001636505,0.003618301,0.00001904065,0.001573077,0.000005796036],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979615,0.0004854789,0.0001979751,0.00005322232,0.000002665729,0.00001660609,0.0006538427,0.000008557676,0.0006201247],"genre_scores_gemma":[0.9980705,0.0003595677,0.000534157,0.00003585273,0.000003003051,0.00001118489,0.0007652522,0.000003584594,0.0002168433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02272485,"threshold_uncertainty_score":0.04518515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0235061111204774,"score_gpt":0.3223262243502231,"score_spread":0.2988201132297457,"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."}}