{"id":"W7099439550","doi":"","title":"Travel time estimation for ambulances using Bayesian data augmentation. Annals of Applied Statistics, to appear","year":2013,"lang":"en","type":"article","venue":"","topic":"Economic, Social, and Public Health Issues in Russia and Globally","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Global Positioning System; Bayesian probability; Interval (graph theory); Estimation; Travel time; Confidence interval; Trajectory; Interval estimation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002109471,0.0001065964,0.0003202139,0.0001277313,0.0001654162,0.0002537175,0.000739116,0.00006302988,0.002479944],"category_scores_gemma":[0.0007265995,0.00008604064,0.00003043567,0.0002244444,0.00006476025,0.000478619,0.00009369264,0.00003366014,0.0004778208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001970085,"about_ca_system_score_gemma":0.0001810082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005483527,"about_ca_topic_score_gemma":0.00004187454,"domain_scores_codex":[0.9980499,0.00005024699,0.0008421391,0.0004016758,0.0003838482,0.0002721816],"domain_scores_gemma":[0.9979799,0.0006963969,0.0003018316,0.0005343503,0.0002900907,0.0001974069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007451577,0.00009554166,0.0004114524,0.00006605536,0.00004645556,2.108501e-7,0.002167561,0.002655538,0.0003012406,0.1193561,0.5578918,0.3169335],"study_design_scores_gemma":[0.0005331726,0.0001226721,0.008686668,0.0000181548,0.00001408806,6.758963e-7,0.002344853,0.7482088,0.0004409689,0.2168255,0.02251794,0.0002865009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01355524,0.00002608131,0.9564852,0.003896421,0.000287807,0.001095605,0.001010378,0.00002256073,0.02362077],"genre_scores_gemma":[0.3715707,0.00001062965,0.6215944,0.003764867,0.0002188891,0.0000436636,0.0003197835,0.00001569641,0.002461331],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7455533,"threshold_uncertainty_score":0.9984319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3098580958567476,"score_gpt":0.4899680142810063,"score_spread":0.1801099184242587,"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."}}