{"id":"W4220861525","doi":"10.1099/mgen.0.000747","title":"regentrans: a framework and R package for using genomics to study regional pathogen transmission","year":2022,"lang":"en","type":"article","venue":"Microbial Genomics","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Human Genome Research Institute; National Institute of Allergy and Infectious Diseases; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Transmission (telecommunications); Genome; Genomics; Computer science; Computational biology; Data science; Biology; Telecommunications; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002589609,0.000184778,0.0001920251,0.00004221821,0.0003836508,0.00004170865,0.0002569343,0.00009884751,0.0000245621],"category_scores_gemma":[0.0000153178,0.0002128334,0.00009317306,0.00007438403,0.00004067917,0.000002582649,0.0001796497,0.000110643,0.000001080361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009306598,"about_ca_system_score_gemma":0.0001214546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009182692,"about_ca_topic_score_gemma":0.000008245143,"domain_scores_codex":[0.998766,0.00008164021,0.0002646328,0.0005137736,0.00007760153,0.0002963746],"domain_scores_gemma":[0.9994326,0.00001517976,0.00007758408,0.0003325749,0.00003604067,0.0001060056],"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":[0.0007181474,0.0001414492,0.0006111423,0.0000166906,0.00006151936,0.000005360806,0.001067667,0.0003158543,0.9953288,0.00003240633,0.00042491,0.001276016],"study_design_scores_gemma":[0.00349829,0.002462411,0.002703887,0.00003702518,0.0002555811,0.0002263152,0.004595043,0.0002213392,0.361318,0.0006500914,0.622656,0.001375936],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8813385,0.0005021185,0.116583,0.0001208112,0.0001659921,0.000973753,0.000302083,0.000008188893,0.000005612994],"genre_scores_gemma":[0.9224508,0.00008358967,0.07589866,0.0008725272,0.0003003045,0.00003016818,0.0001906817,0.000073335,0.00009989399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6340109,"threshold_uncertainty_score":0.8679096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01876917729205897,"score_gpt":0.2624466408676545,"score_spread":0.2436774635755956,"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."}}