{"id":"W4391386575","doi":"10.1128/mra.01242-23","title":"Complete genome sequences of a Canadian strain of enteroaggregative <i>Escherichia coli</i> (EAEC) with multiple metals and antimicrobial resistance genes isolated from municipal waste-activated sludge","year":2024,"lang":"en","type":"article","venue":"Microbiology Resource Announcements","topic":"Enterobacteriaceae and Cronobacter Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Food Inspection Agency","funders":"Canadian Food Inspection Agency","keywords":"Enteroaggregative Escherichia coli; Microbiology; Antimicrobial; Escherichia coli; Strain (injury); Whole genome sequencing; Biology; Gene; Genome; Antibiotic resistance; Activated sludge; Pathogen; Sewage treatment; Enterobacteriaceae; Genetics; Antibiotics; Waste management","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":[0.0003713603,0.001435447,0.0009050437,0.002425553,0.001800633,0.001135648,0.001111036,0.0008196434,0.003524053],"category_scores_gemma":[0.001016352,0.0004162607,0.0009522575,0.005702213,0.0005369999,0.0004553761,0.0006696287,0.001596354,0.002253815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00379948,"about_ca_system_score_gemma":0.01776985,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5803721,"about_ca_topic_score_gemma":0.6185594,"domain_scores_codex":[0.9994401,0.00002149645,0.00002872149,0.00009070605,0.000287022,0.0001319623],"domain_scores_gemma":[0.9989071,0.00007626596,0.0001461557,0.00006109328,0.0005844663,0.0002249636],"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":[0.001840893,0.0003467674,0.007133573,0.001612141,0.00015025,0.001099042,0.0009444823,0.001338743,0.9209574,0.001083587,0.01989324,0.04359977],"study_design_scores_gemma":[0.0003861132,0.0007392949,0.3610466,0.0003714713,0.001012192,0.002329828,0.001908544,0.002499463,0.1510685,0.0008743878,0.4773534,0.000410242],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3137122,0.005924319,0.01204162,0.001514915,0.0004717901,0.0008095981,0.6480398,0.001113117,0.01637255],"genre_scores_gemma":[0.1291035,0.004461587,0.02396887,0.0004068219,0.00007956044,0.000246957,0.8286608,0.0003323572,0.01273951],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4196279,"threshold_uncertainty_score":0.8441983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0176082207939101,"score_gpt":0.2344105826149162,"score_spread":0.2168023618210061,"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."}}