{"id":"W4391449885","doi":"10.1128/mra.01149-23","title":"Complete genome sequence of multidrug-resistant <i>Enterobacter roggenkampii</i> 0-E","year":2024,"lang":"en","type":"article","venue":"Microbiology Resource Announcements","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs; Ministère des Ressources naturelles et des Forêts; Université Laval","funders":"Canadian Institutes of Health Research; Government of Canada","keywords":"Enterobacter cloacae; Genome; Multiple drug resistance; Whole genome sequencing; Enterobacter; Biology; Nanopore sequencing; Gene; Genetics; Computational biology; Drug resistance; Enterobacteriaceae; Escherichia coli","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003588177,0.0008047958,0.0008485342,0.001167684,0.0005855505,0.0007644555,0.0004568147,0.0008456031,0.004272486],"category_scores_gemma":[0.001048039,0.0003967161,0.0006698405,0.00201206,0.0002833353,0.0004547113,0.000727497,0.001008158,0.00439491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000500118,"about_ca_system_score_gemma":0.001422343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006417479,"about_ca_topic_score_gemma":0.007083702,"domain_scores_codex":[0.9996163,0.00003821109,0.0000376987,0.0001278809,0.0001067066,0.0000733605],"domain_scores_gemma":[0.999423,0.0001361172,0.0000978513,0.00005832918,0.0001723202,0.000112485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001960791,0.0001279721,0.007163344,0.002174459,0.0000999762,0.0007746858,0.0004864954,0.001330404,0.9415294,0.000842858,0.01267364,0.03083596],"study_design_scores_gemma":[0.0003782797,0.0009394325,0.2830594,0.001139293,0.0005221549,0.002544021,0.00146245,0.004429287,0.2772708,0.001758323,0.4261817,0.0003148358],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.3957522,0.004956211,0.02262052,0.0009307096,0.0003681346,0.0003635734,0.5622893,0.002012572,0.01070681],"genre_scores_gemma":[0.1603662,0.002086905,0.03923869,0.0004221584,0.00006581801,0.0002347885,0.7899669,0.0007630949,0.006855507],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006417479,"threshold_uncertainty_score":0.0142929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750351120624959,"score_gpt":0.2549689964540826,"score_spread":0.237465485247833,"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."}}