{"id":"W2116623092","doi":"10.1093/molbev/msu121","title":"Bayesian Inference of Infectious Disease Transmission from Whole-Genome Sequence Data","year":2014,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":223,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Centre for Disease Control; University of British Columbia","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; National Institute for Health and Care Research","keywords":"Biology; Markov chain Monte Carlo; Genomics; Bayesian probability; Evolutionary biology; Inference; Computational biology; Population genomics; Bayesian inference; Population; Genome; Genetics; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001380349,0.0001287326,0.0001437511,0.00003122289,0.000078176,0.000005826108,0.0001976585,0.0001290213,0.000003711298],"category_scores_gemma":[0.00009849127,0.0001198428,0.00003538477,0.00004731919,0.0001848836,0.000001625265,0.0001981068,0.00005475694,0.000001464223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005989452,"about_ca_system_score_gemma":0.00004316143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001115897,"about_ca_topic_score_gemma":0.00001914782,"domain_scores_codex":[0.9991085,0.0001148652,0.0001637783,0.0004150621,0.00004299319,0.0001547839],"domain_scores_gemma":[0.9993078,0.00001644289,0.00006969945,0.000473771,0.00004594753,0.00008640638],"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":[0.00004568052,0.00002283484,0.04457982,0.00001177729,0.00004391965,5.84847e-7,0.0000168678,0.0001194221,0.9514934,0.0006475312,0.00001206505,0.00300614],"study_design_scores_gemma":[0.002935459,0.0017933,0.7313051,0.00009320667,0.0003999723,0.00001567267,0.00005590669,0.01762311,0.07602292,0.06927467,0.09910735,0.001373325],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6715881,0.003599711,0.3241968,0.0001031215,0.00006971259,0.00007870137,0.0002766441,0.000003644943,0.00008353136],"genre_scores_gemma":[0.9969949,0.0003964037,0.001197908,0.00009847213,0.00006563465,0.000006621907,0.001214943,0.000009017121,0.00001607919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8754704,"threshold_uncertainty_score":0.4887048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01225546447815746,"score_gpt":0.2631258791246235,"score_spread":0.2508704146464661,"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."}}