{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003869963,0.00008461293,0.0001870696,0.00003367456,0.0001197257,0.00001308834,0.0001178754,0.00004226654,0.000001612883],"category_scores_gemma":[0.00003113778,0.00007434609,0.00003595169,0.00008236544,0.00007236846,0.000006036825,0.0000572476,0.00004330679,6.798183e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003554721,"about_ca_system_score_gemma":0.0000543691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002662854,"about_ca_topic_score_gemma":0.0001392042,"domain_scores_codex":[0.9992294,0.00007197679,0.0003365917,0.0001700963,0.0000766955,0.0001152711],"domain_scores_gemma":[0.9994512,0.00002171484,0.0002800896,0.0001865044,0.00004867015,0.00001182202],"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":[0.0001299851,0.00001013609,0.02287482,0.0002513084,0.00001864072,3.411518e-7,0.0001299246,0.00005108914,0.9755586,0.000006099279,0.000008894522,0.0009601727],"study_design_scores_gemma":[0.0003547703,0.000160549,0.03909433,0.00003854592,0.00002806709,0.000005983674,0.0003619743,0.003633501,0.953163,9.608463e-7,0.003032587,0.0001257269],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974424,0.001268674,0.0005667459,0.000008369766,0.0002556842,0.0003827633,0.00006153754,0.000002168293,0.00001161681],"genre_scores_gemma":[0.9990708,0.0003577438,0.0002084117,0.00001244572,0.00008889579,0.00003678965,0.00001794776,0.00001309114,0.0001939265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02239558,"threshold_uncertainty_score":0.3031746,"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."}}