{"id":"W2739559315","doi":"10.1093/femsle/fnx161","title":"Comparative genomics of a drug-resistant Pseudomonas aeruginosa panel and the challenges of antimicrobial resistance prediction from genomes","year":2017,"lang":"en","type":"article","venue":"FEMS Microbiology Letters","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Canadian Institutes of Health Research; Joint Programming Initiative on Antimicrobial Resistance; Cystic Fibrosis Canada; Genome Canada; World Health Organization","keywords":"Pseudomonas aeruginosa; Resistome; Genome; Biology; Genomics; Antibiotic resistance; Whole genome sequencing; Comparative genomics; Computational biology; Genetics; Drug resistance; Gene; Microbiology; Antibiotics; Bacteria; Mobile genetic elements","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":[0.0006782602,0.0003663441,0.0005001635,0.001108616,0.0003500561,0.0007542605,0.0002532182,0.000368897,0.0006884696],"category_scores_gemma":[0.001345688,0.0001292487,0.0005284157,0.001384779,0.00015078,0.00035557,0.0005301344,0.0005117815,0.0003578888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000288431,"about_ca_system_score_gemma":0.0002843007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001749151,"about_ca_topic_score_gemma":0.002487225,"domain_scores_codex":[0.9993312,0.0002640173,0.00003897964,0.0001396229,0.0001503495,0.00007587559],"domain_scores_gemma":[0.9993978,0.0002587053,0.00007448256,0.00007558943,0.0001366619,0.0000568077],"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":[0.0002676934,0.00009442999,0.01305309,0.0001161639,0.00006595319,0.0002648193,0.0001979053,0.001628656,0.9677912,0.0002586991,0.0003392057,0.01592216],"study_design_scores_gemma":[0.00004583611,0.001747468,0.5381288,0.0001287893,0.0004692769,0.003203843,0.001877898,0.03467853,0.3955676,0.002051824,0.02199712,0.0001029608],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812363,0.0005873548,0.01187071,0.0003908696,0.00002033437,0.00004261074,0.004376248,0.0001197061,0.001355667],"genre_scores_gemma":[0.947401,0.0007373705,0.0323981,0.000205722,0.00002316026,0.00008261627,0.0185334,0.00009990032,0.000518596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001749151,"threshold_uncertainty_score":0.003587008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01751150338305087,"score_gpt":0.2308109095153695,"score_spread":0.2132994061323187,"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."}}