{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001553957,0.0002672182,0.0003923771,0.0002002492,0.00009176989,0.00004035217,0.000314633,0.00018652,0.00003596294],"category_scores_gemma":[0.00001126732,0.0002292568,0.00007249752,0.0002794355,0.0005517985,0.0000143006,0.0001502454,0.0001552996,0.000003063368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003444226,"about_ca_system_score_gemma":0.0001583531,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01003714,"about_ca_topic_score_gemma":0.03748124,"domain_scores_codex":[0.9983432,0.0002274576,0.0003779548,0.000547396,0.00006995944,0.0004340184],"domain_scores_gemma":[0.9992716,0.0000297162,0.0001533023,0.0003142091,0.0001173398,0.0001138252],"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":[0.0007590484,0.00005182141,0.004361836,0.00009610713,0.0006746723,0.00001746688,0.000723564,0.00002104684,0.993027,0.000001823822,0.0002231846,0.00004244438],"study_design_scores_gemma":[0.00127466,0.0007783499,0.0005947779,0.0003009404,0.0000796985,0.00001746105,0.0009775633,0.00002783113,0.8135079,0.000002764246,0.1821105,0.0003275331],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797009,0.002601386,0.00007348767,0.0001148936,0.00004482116,0.000348021,0.01699832,0.00001010743,0.0001080512],"genre_scores_gemma":[0.9902169,0.0003285359,0.0004478841,0.0001632698,0.00003970933,0.00001814654,0.008420045,0.0000304778,0.000335054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1818873,"threshold_uncertainty_score":0.9965551,"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."}}