{"id":"W2148841109","doi":"10.1128/aem.00137-06","title":"A Virulence and Antimicrobial Resistance DNA Microarray Detects a High Frequency of Virulence Genes in <i>Escherichia coli</i> Isolates from Great Lakes Recreational Waters","year":2006,"lang":"en","type":"article","venue":"Applied and Environmental Microbiology","topic":"Escherichia coli research studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ste. Anne's Hospital; Environment and Climate Change Canada; Université de Montréal; Biotechnology Research Institute","funders":"Canadian Water Network","keywords":"Virulence; Biology; Escherichia coli; Microbiology; Gene; DNA microarray; Antibiotic resistance; Microarray; Pathogenic Escherichia coli; Genetics; Antimicrobial; Bacteria; Gene expression","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":[0.00008710547,0.0002323595,0.000274307,0.00004142073,0.0000944187,0.00001213542,0.0001384547,0.0001828057,0.00001244723],"category_scores_gemma":[0.000006522758,0.0002200258,0.00003245922,0.00005649899,0.0007615639,0.000007842686,0.0001950956,0.000104614,0.00000280555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002652232,"about_ca_system_score_gemma":0.00002028393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004000463,"about_ca_topic_score_gemma":0.0005708901,"domain_scores_codex":[0.9987594,0.00006477172,0.0002724635,0.0005483328,0.00004002506,0.0003150092],"domain_scores_gemma":[0.9996415,0.00004063396,0.00009525607,0.000172555,0.000006906032,0.00004308947],"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":[0.000163901,0.00006618726,0.03202932,0.00002767399,0.00003886619,0.000002720883,0.00005348304,0.000006838462,0.9673175,0.00003983786,0.00008313095,0.0001705271],"study_design_scores_gemma":[0.0009100299,0.00007712923,0.05847653,0.00002906417,0.00001549091,0.000006606651,0.00007418806,0.000002359433,0.9390037,0.000231806,0.0009240367,0.0002490659],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955038,0.003568761,0.00005062464,0.00007713811,0.00002971589,0.0002508691,0.0003923172,0.000006442504,0.0001202744],"genre_scores_gemma":[0.9937065,0.002812939,0.002699952,0.0001627527,0.00005218757,0.00004520549,0.0004154284,0.00001840614,0.0000866261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02831382,"threshold_uncertainty_score":0.8972392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003438494869066098,"score_gpt":0.1773382868617644,"score_spread":0.1738997919926983,"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."}}