{"id":"W2885756312","doi":"10.1016/j.aap.2018.08.004","title":"Bivariate extreme value modeling for road safety estimation","year":2018,"lang":"en","type":"article","venue":"Accident Analysis & Prevention","topic":"Traffic and Road Safety","field":"Engineering","cited_by":110,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia Hospital; Carleton University; University of British Columbia","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Bivariate analysis; Univariate; Extreme value theory; Generalized Pareto distribution; Statistics; Generalized extreme value distribution; Econometrics; Multivariate statistics; Poison control; Crash; Computer science; Mathematics","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":[0.009657274,0.001230713,0.002587427,0.001443713,0.0006551435,0.001555001,0.002661805,0.001914642,0.003571578],"category_scores_gemma":[0.03639687,0.001275221,0.002253559,0.002296147,0.001517534,0.002167989,0.002335704,0.003885237,0.0008158607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007734874,"about_ca_system_score_gemma":0.001367416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006088815,"about_ca_topic_score_gemma":0.003761736,"domain_scores_codex":[0.9943343,0.004245236,0.0001448001,0.000547177,0.0003784304,0.0003498848],"domain_scores_gemma":[0.9757364,0.02052668,0.0009452782,0.001568749,0.0009261979,0.0002965556],"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":[0.0001697059,0.0001229676,0.00393916,0.00009374473,0.0002693867,0.0000973572,0.00009574185,0.8704719,0.0005194655,0.07370193,0.002105955,0.0484127],"study_design_scores_gemma":[0.000006619639,0.00001719901,0.0004215229,0.0000095626,0.00001726511,0.00001186472,0.000009828669,0.9717597,0.0001170921,0.02729304,0.0003247978,0.00001155056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005731685,0.0001671331,0.9935236,0.0001115253,0.00002373634,0.00001186085,0.00007644958,0.0001182265,0.000235875],"genre_scores_gemma":[0.7283469,0.001388359,0.2591112,0.0002788295,0.0003329179,0.0003907341,0.001743519,0.0003015029,0.008106019],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009657274,"threshold_uncertainty_score":0.05107319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02400277967295574,"score_gpt":0.2693995232184203,"score_spread":0.2453967435454646,"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."}}