{"id":"W4281820925","doi":"10.1128/msystems.00022-22","title":"Performance Characteristics of Next-Generation Sequencing for the Detection of Antimicrobial Resistance Determinants in Escherichia coli Genomes and Metagenomes","year":2022,"lang":"en","type":"article","venue":"mSystems","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University Health Network; University of Toronto; Toronto General Hospital; Public Health Ontario; McMaster University","funders":"Cisco Systems Canada; Physicians' Services Incorporated Foundation; Government of Canada; Canadian Institutes of Health Research; Ontario Genomics; University of Guelph; Natural Sciences and Engineering Research Council of Canada; McMaster University; Cisco Systems","keywords":"Metagenomics; Escherichia coli; Biology; Computational biology; Genome; DNA sequencing; Antibiotic resistance; Benchmark (surveying); Genetics; Gene; Bacteria; Geography","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":[0.00458428,0.0007560307,0.0004203383,0.0007746067,0.0004376922,0.001103734,0.000454578,0.0010263,0.0007741949],"category_scores_gemma":[0.0081511,0.0002720405,0.000369754,0.0006239453,0.0003650982,0.0008919214,0.0005394557,0.0005687198,0.0004712103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000717015,"about_ca_system_score_gemma":0.0005259494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002265658,"about_ca_topic_score_gemma":0.002359832,"domain_scores_codex":[0.9973699,0.0007157043,0.0001534594,0.0004238259,0.001074531,0.0002624433],"domain_scores_gemma":[0.9960932,0.002164008,0.0003945114,0.000197256,0.0009467545,0.0002043655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003309438,0.0000755209,0.01056067,0.0001289223,0.00005818392,0.0000359314,0.0001203754,0.004883358,0.9697817,0.0003460385,0.0002494871,0.01342884],"study_design_scores_gemma":[0.000006420804,0.0005471966,0.02533376,0.00002646992,0.00005351755,0.0001691808,0.0001168966,0.03685593,0.9341545,0.0002759147,0.002404855,0.0000552385],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8914421,0.002083499,0.1019194,0.0004047455,0.00005808745,0.0000967055,0.000963873,0.0007377212,0.00229395],"genre_scores_gemma":[0.9460559,0.0006789382,0.05001438,0.000244594,0.00002748795,0.0001059957,0.001625459,0.0001704582,0.001076718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00458428,"threshold_uncertainty_score":0.02424431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02798993004090993,"score_gpt":0.2353938002713361,"score_spread":0.2074038702304262,"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."}}