{"id":"W3209352051","doi":"10.1099/mgen.0.000672","title":"Evaluation of whole-genome sequencing-based subtyping methods for the surveillance of Shigella spp. and the confounding effect of mobile genetic elements in long-term outbreaks","year":2021,"lang":"en","type":"article","venue":"Microbial Genomics","topic":"Escherichia coli research studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Montréal; Centre Hospitalier de l’Université de Montréal; Ste. Anne's Hospital","funders":"","keywords":"Subtyping; Outbreak; Multilocus sequence typing; Shigella sonnei; Biology; Whole genome sequencing; Genetics; Shigellosis; Typing; Shigella; Genome; Virology; Genotype; Salmonella; Gene; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.005340949,0.0001161616,0.000306687,0.00003064508,0.00005903636,0.00001243066,0.0001784762,0.00006471795,0.000003972839],"category_scores_gemma":[0.0006615529,0.00008273891,0.00009729008,0.0001061407,0.0002642571,0.000001698932,0.0001614813,0.00006579889,1.079659e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006888901,"about_ca_system_score_gemma":0.0003762531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005123878,"about_ca_topic_score_gemma":0.0003394965,"domain_scores_codex":[0.9981784,0.0009138259,0.0003861982,0.0002165162,0.0001253982,0.0001796618],"domain_scores_gemma":[0.9986421,0.0004417661,0.0002288556,0.0002918053,0.000378611,0.00001686186],"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":[0.0002935919,0.00001580936,0.01132972,0.0002231566,0.0001566206,2.146457e-7,0.0001826127,0.003631507,0.9779507,0.000002568384,0.000002173594,0.006211356],"study_design_scores_gemma":[0.003859812,0.0002564373,0.02037838,0.0000385474,0.0001348802,0.000002830546,0.0001067815,0.005693991,0.9691177,0.00001608577,0.0002881101,0.0001064272],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821465,0.01085401,0.005721946,0.00002714606,0.00006599427,0.001105334,0.00006095807,0.000001049061,0.00001708336],"genre_scores_gemma":[0.9963655,0.0005471872,0.00285248,0.00002100971,0.0000393408,0.00009211063,0.00005420428,0.00001477001,0.00001334522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01421907,"threshold_uncertainty_score":0.3373995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02495348164995905,"score_gpt":0.3585431468141583,"score_spread":0.3335896651641992,"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."}}