{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001666484,0.0001070918,0.0001873546,0.00001294465,0.00003973613,0.00001005102,0.00009019209,0.0001261733,0.000006225769],"category_scores_gemma":[0.0001736197,0.0001073705,0.00003092251,0.00004552179,0.0001065912,0.000003086702,0.00009638924,0.00005830949,0.000002348934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001501191,"about_ca_system_score_gemma":0.00004939163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008892628,"about_ca_topic_score_gemma":0.00001497653,"domain_scores_codex":[0.999265,0.00007195908,0.0001851246,0.0003135539,0.0000252082,0.0001391651],"domain_scores_gemma":[0.9996647,0.00002245791,0.0000701398,0.0001053746,0.00004548395,0.00009181217],"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":[0.0003933958,0.000008202494,0.05035555,0.00003931769,0.00001136804,0.000001027822,0.00003978801,0.00004233179,0.9485813,0.00001040244,0.0003486598,0.000168644],"study_design_scores_gemma":[0.001933873,0.0007547432,0.4625699,0.00005581044,0.00002957987,0.00001574281,0.0001286693,0.003483575,0.4744743,0.00001133094,0.05608387,0.0004586438],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959072,0.0002822684,0.002436844,0.0005851645,0.0000607482,0.0001776002,0.0005076947,0.000008447376,0.00003405738],"genre_scores_gemma":[0.9974228,0.0001485018,0.001767624,0.0004769768,0.00009244068,6.225146e-7,0.00006923193,0.0000091213,0.00001273386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.474107,"threshold_uncertainty_score":0.4378442,"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."}}