{"id":"W4241761139","doi":"10.21203/rs.3.rs-78954/v1","title":"Population genomics provides insights in diversity, epidemiology, evolution and pathogenicity of the waterborne pathogen Mycobacterium kansasii","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Mycobacterium research and diagnosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Sanming Project of Medicine in Shenzhen; National Health and Medical Research Council; Medical Research Council; National Science and Technology Major Project; National Key Research and Development Program of China; Canadian Institutes of Health Research; Department of Science and Technology of Sichuan Province; National Natural Science Foundation of China","keywords":"Mycobacterium kansasii; Pathogenicity; Genomics; Pathogen; Diversity (politics); Biology; Population; Population genomics; Epidemiology; Microbiology; Molecular epidemiology; Mycobacterium; Genotype; Genetics; Genome; Medicine; Environmental health; Gene; Bacteria; Pathology","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":[0.000569903,0.0002087825,0.0002385219,0.0005219422,0.0003147763,0.001043918,0.0001915862,0.0006666423,0.001367369],"category_scores_gemma":[0.001422341,0.0002199563,0.0002018906,0.0005763582,0.0003558363,0.0006189083,0.0004117592,0.0008183367,0.0002917345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003166171,"about_ca_system_score_gemma":0.0002055918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001953369,"about_ca_topic_score_gemma":0.001766984,"domain_scores_codex":[0.99978,0.00004685659,0.000005834509,0.00008734733,0.0000425688,0.00003739476],"domain_scores_gemma":[0.9995709,0.0002557957,0.00005733584,0.00004190054,0.00004018817,0.00003387712],"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":[0.000707788,0.0002429927,0.2142097,0.0003589068,0.0003118038,0.0005316912,0.003324765,0.01622703,0.6009874,0.01685225,0.003643544,0.1426022],"study_design_scores_gemma":[0.00005739395,0.000318342,0.8569621,0.00009078813,0.0002246634,0.0009527204,0.002266509,0.04596895,0.03344328,0.03266736,0.02696641,0.00008144671],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871473,0.0004940888,0.0085377,0.0005746225,0.00003469206,0.000005361999,0.0006717589,0.00008325036,0.002451256],"genre_scores_gemma":[0.9949549,0.0003555492,0.002971177,0.0001567273,0.00004520721,0.000004841686,0.0006620332,0.00003675141,0.0008128157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001953369,"threshold_uncertainty_score":0.004574299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1009181888686344,"score_gpt":0.36553188886619,"score_spread":0.2646136999975556,"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."}}