{"id":"W2100378151","doi":"10.1093/molbev/msv123","title":"Phylodynamic Inference with Kernel ABC and Its Application to HIV Epidemiology","year":2015,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; AIDS Vancouver; Simon Fraser University","funders":"Canadian Institutes of Health Research; Michael Smith Health Research BC; Providence Health Care; St. Paul's Foundation; Bill and Melinda Gates Foundation","keywords":"Approximate Bayesian computation; Inference; Kernel (algebra); Viral phylodynamics; Biology; Phylogenetic tree; Tree (set theory); Computer science; Computational biology; Artificial intelligence; Mathematics; Genetics","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":[0.0002403868,0.0001420368,0.0001648343,0.00004086649,0.00007408042,0.00000379206,0.00007429788,0.0001613298,4.309786e-7],"category_scores_gemma":[0.0001568892,0.0001209184,0.00001818606,0.00006124859,0.0001178512,9.870289e-7,0.0001313484,0.00005635139,0.000007722088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000141865,"about_ca_system_score_gemma":0.00003853307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003239495,"about_ca_topic_score_gemma":0.00004586807,"domain_scores_codex":[0.9991066,0.0001016353,0.0001390624,0.0004084474,0.0000252003,0.0002190321],"domain_scores_gemma":[0.9995337,0.00001731115,0.00005656248,0.0001684887,0.00009342938,0.0001305215],"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":[0.0001423872,0.00002056439,0.1250039,0.000009492159,0.00005935942,7.08467e-7,0.00005789722,0.0005289575,0.8581761,0.01450181,0.0000752819,0.001423562],"study_design_scores_gemma":[0.003969056,0.005405168,0.8493952,0.00004380932,0.000193358,0.0002296365,0.0004132955,0.01011351,0.04819608,0.05309668,0.02723391,0.001710269],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8705438,0.00471567,0.1237545,0.0005159759,0.00003829988,0.0002042244,0.00001466487,0.000005081317,0.0002077311],"genre_scores_gemma":[0.9975275,0.0001720171,0.001646679,0.0004195351,0.00005397877,0.00006209702,0.00006130729,0.0000101225,0.0000467814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.80998,"threshold_uncertainty_score":0.493091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01238093657594431,"score_gpt":0.2784302010402885,"score_spread":0.2660492644643442,"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."}}