{"id":"W3088602524","doi":"10.1099/mgen.0.000435","title":"Universal whole-sequence-based plasmid typing and its utility to prediction of host range and epidemiological surveillance","year":2020,"lang":"en","type":"article","venue":"Microbial Genomics","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":162,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada","funders":"Public Health Agency of Canada","keywords":"Typing; Host (biology); Sequence (biology); Plasmid; Computational biology; Epidemiology; Computer science; Biology; Genetics; Medicine; Gene","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":[0.003535947,0.0009788447,0.001202084,0.004233768,0.0004547009,0.001608201,0.0009840179,0.0007850051,0.002008826],"category_scores_gemma":[0.01155499,0.0004443382,0.0009663413,0.0039631,0.0004298778,0.001341837,0.001790065,0.0009622089,0.00192393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004857439,"about_ca_system_score_gemma":0.000929799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002096478,"about_ca_topic_score_gemma":0.002282819,"domain_scores_codex":[0.9977133,0.0006009554,0.0002360719,0.0007385401,0.0005038079,0.0002072918],"domain_scores_gemma":[0.9932974,0.002087181,0.001889098,0.0007571751,0.001402384,0.0005667582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002501919,0.0004575658,0.4108576,0.00237016,0.000587269,0.0006400397,0.001328731,0.02214292,0.25589,0.004274529,0.009179672,0.2897695],"study_design_scores_gemma":[0.0001228277,0.00128634,0.4116227,0.0008636286,0.0006774744,0.002741653,0.001421693,0.362901,0.150717,0.01565269,0.05157759,0.0004155382],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6914963,0.003660557,0.2703188,0.0003709972,0.000157726,0.0002884962,0.02459773,0.004469026,0.004640489],"genre_scores_gemma":[0.6866739,0.001251712,0.281209,0.0001883365,0.00006853371,0.0002952018,0.02848094,0.0005689661,0.001263463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004233768,"threshold_uncertainty_score":0.01870006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03315186555051549,"score_gpt":0.2400241374756805,"score_spread":0.206872271925165,"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."}}