{"id":"W4312191616","doi":"10.1093/ve/veac120","title":"bayroot: Bayesian sampling of HIV-1 integration dates by root-to-tip regression","year":2022,"lang":"en","type":"article","venue":"Virus Evolution","topic":"HIV Research and Treatment","field":"Immunology and Microbiology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Institute of Allergy and Infectious Diseases","keywords":"Bayesian probability; Sampling (signal processing); Human immunodeficiency virus (HIV); Root (linguistics); Statistics; Regression; Econometrics; Computer science; Mathematics; Biology; Virology; Linguistics; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00850059,0.0008407002,0.001489115,0.001318179,0.0009299191,0.00138582,0.003003967,0.001615368,0.00973272],"category_scores_gemma":[0.03486971,0.001085488,0.001282153,0.001424963,0.001199996,0.001887963,0.001526967,0.002873803,0.002340469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001141499,"about_ca_system_score_gemma":0.001382711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009607579,"about_ca_topic_score_gemma":0.009991025,"domain_scores_codex":[0.997437,0.001684219,0.00008672653,0.0003534469,0.0003288036,0.0001098995],"domain_scores_gemma":[0.986347,0.01076211,0.000771797,0.001012908,0.000816203,0.0002899524],"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":[0.0008744603,0.0001665004,0.01239342,0.000359595,0.0003082713,0.0002521417,0.0004533451,0.8490075,0.006144822,0.04258308,0.007603847,0.07985306],"study_design_scores_gemma":[0.00008727048,0.00003139006,0.0005919659,0.00001749658,0.00001780026,0.00004065857,0.00002007007,0.9870077,0.001003015,0.00996588,0.001197435,0.00001929865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08482298,0.0003852676,0.9048228,0.0002664478,0.00007301304,0.000148339,0.001047023,0.006729771,0.001704385],"genre_scores_gemma":[0.4166458,0.000265812,0.5748414,0.000268699,0.00007142836,0.0003569676,0.002706275,0.00244536,0.002398286],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00973272,"threshold_uncertainty_score":0.04495597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01745796460515206,"score_gpt":0.2801368646007391,"score_spread":0.262678899995587,"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."}}