{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005693039,0.000368095,0.001041887,0.001886343,0.0008248259,0.001431737,0.001379417,0.001070746,0.001339799],"category_scores_gemma":[0.04032836,0.0004824904,0.0007849606,0.001763922,0.001387578,0.001898183,0.001720406,0.001464339,0.0001872333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001510083,"about_ca_system_score_gemma":0.001502353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01298496,"about_ca_topic_score_gemma":0.006755569,"domain_scores_codex":[0.997447,0.001770176,0.0001330476,0.0002490906,0.0003118468,0.00008884785],"domain_scores_gemma":[0.9759229,0.0199438,0.0009742262,0.001356586,0.001529293,0.0002731346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006817171,0.00004876242,0.006798123,0.00008472351,0.00009958641,0.0001086337,0.0002192206,0.787481,0.0008922484,0.1298267,0.0006869076,0.07368593],"study_design_scores_gemma":[0.000003426538,0.000003610561,0.0002305428,0.000003014807,0.000003196188,0.00001246331,0.000007221319,0.9762627,0.0000895277,0.02319898,0.0001812339,0.000004073782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02733668,0.0001617174,0.971401,0.0002556041,0.00001494753,0.00001701482,0.00004074588,0.0001832211,0.000589047],"genre_scores_gemma":[0.6348993,0.0002531991,0.3634697,0.0001370412,0.00004919309,0.00009493119,0.0001637091,0.00009882134,0.0008342027],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01298496,"threshold_uncertainty_score":0.03010798,"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."}}