{"id":"W2914889663","doi":"10.1371/journal.pone.0211144","title":"Functional screening for triclosan resistance in a wastewater metagenome and isolates of Escherichia coli and Enterococcus spp. from a large Canadian healthcare region","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Antimicrobial agents and applications","field":"Chemistry","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Calgary Laboratory Services; University of Calgary","funders":"Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada; Beef Cattle Research Council; Inha University; Calgary Laboratory Services; University of Manitoba; Alberta Agriculture and Forestry; Public Health Agency of Canada","keywords":"Triclosan; Microbiology; Enterococcus faecium; Biology; Enterococcus faecalis; Escherichia coli; Antibiotic resistance; Enterococcus; Drug resistance; Resistome; Teicoplanin; Vancomycin; Bacteria; Antibiotics; Genetics; Staphylococcus aureus; Medicine; Integron","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002443625,0.0004507365,0.0004227724,0.0007962073,0.0004994184,0.0004806474,0.000294446,0.0002651458,0.0006990996],"category_scores_gemma":[0.000587438,0.0001832558,0.000453983,0.001404216,0.0002274021,0.0001705271,0.0005249237,0.0003177644,0.0002160495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001019067,"about_ca_system_score_gemma":0.001631292,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1425919,"about_ca_topic_score_gemma":0.1898039,"domain_scores_codex":[0.9995415,0.0000214245,0.0000241604,0.0001081677,0.0002151579,0.00008958975],"domain_scores_gemma":[0.9996953,0.00002857986,0.00004285716,0.00001696957,0.0001705003,0.00004577872],"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":[0.0001647601,0.00006980427,0.04321783,0.0001100434,0.00004727835,0.0001060847,0.0002986545,0.0001654248,0.9477489,0.00003921195,0.0001128521,0.007919282],"study_design_scores_gemma":[0.00001517509,0.000571726,0.786648,0.00002862965,0.0001765292,0.0009087467,0.001818287,0.002105379,0.2037449,0.00005644934,0.003893215,0.00003290577],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941958,0.0002847768,0.001272984,0.0000786145,0.000004953737,0.0000599661,0.003283766,0.0000360667,0.0007831238],"genre_scores_gemma":[0.981309,0.0005670615,0.006516476,0.0001361506,0.000005150323,0.00005383999,0.008799545,0.00002619034,0.00258668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8574081,"threshold_uncertainty_score":0.2835239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03841876311072773,"score_gpt":0.2173461525875058,"score_spread":0.1789273894767781,"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."}}