{"id":"W2914456697","doi":"10.1007/s00438-019-01531-5","title":"Distinct evolutionary origins of common multi-drug resistance phenotypes in Salmonella typhimurium DT104: a convergent process for adaptation under stress","year":2019,"lang":"en","type":"article","venue":"Molecular Genetics and Genomics","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Agency of Canada; University of Calgary","funders":"Postdoctoral Research Foundation of China; National Natural Science Foundation of China; Alberta Innovates - Health Solutions; Genome Canada","keywords":"Biology; Gene; Plasmid; Phenotype; Salmonella; Genetics; Adaptation (eye); Antibiotic resistance; Drug resistance; Antimicrobial; Bacteria; Bacterial genetics; Antimicrobial drug; Multiple drug resistance; Microbiology; Computational biology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001297937,0.0001243222,0.0002221264,0.0000143492,0.00004125344,0.000009138889,0.0001305809,0.00008165568,0.00001158124],"category_scores_gemma":[0.00001235659,0.00006919826,0.00005277797,0.00009682753,0.00005194998,0.00001613881,0.0000389526,0.0000560184,0.000002412638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004509718,"about_ca_system_score_gemma":0.00001868009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001354823,"about_ca_topic_score_gemma":0.001688919,"domain_scores_codex":[0.9991181,0.00006225431,0.0002697534,0.0002791337,0.00007474433,0.0001960022],"domain_scores_gemma":[0.9995726,0.0001093011,0.0001240109,0.00007141245,0.00007142751,0.0000512002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006279584,0.0006635143,0.4331915,0.0003287063,0.0001011083,0.00000743816,0.00142098,0.02021519,0.5321503,0.005651873,0.00007969476,0.005561715],"study_design_scores_gemma":[0.001040862,0.0002406898,0.9362066,0.00005981593,0.00004556031,0.000002897751,0.001431615,0.02859636,0.01598105,0.01033674,0.005583001,0.0004747887],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959364,0.002753846,0.000399338,0.0002457159,0.00009744018,0.0004091871,0.0001144278,0.000007723224,0.00003592633],"genre_scores_gemma":[0.9986988,0.0002229757,0.0007198847,0.0001016854,0.00002842554,0.0000189044,0.0001402358,0.000002690887,0.00006638356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5161693,"threshold_uncertainty_score":0.2821823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02248962376102198,"score_gpt":0.2505272860226264,"score_spread":0.2280376622616044,"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."}}