{"id":"W2886753453","doi":"10.1155/2018/6964828","title":"The Effects of Traffic Composition on Freeway Crash Frequency by Injury Severity: A Bayesian Multivariate Spatial Modeling Approach","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic and Road Safety","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Crash; Truck; Multivariate statistics; Poison control; Transport engineering; Bayesian probability; Environmental science; Statistics; Computer science; Engineering; Automotive engineering; Mathematics; Medicine; Environmental health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001386815,0.0001472373,0.0002216647,0.00007110757,0.0001143902,0.00001054836,0.0001202909,0.0000842067,0.000002466222],"category_scores_gemma":[0.000009965592,0.0001115021,0.0001080759,0.0001233529,0.00004623878,0.0002336691,8.347477e-7,0.0002495752,7.37885e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005113069,"about_ca_system_score_gemma":0.00002105074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007131255,"about_ca_topic_score_gemma":0.00002605613,"domain_scores_codex":[0.9989087,0.00003555828,0.0005301539,0.000100384,0.0002651898,0.0001600332],"domain_scores_gemma":[0.9994347,0.00007301859,0.000191321,0.0001049067,0.0001333013,0.00006271908],"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":[0.0002749383,0.0001048622,0.00003897431,0.0001273654,0.00007850529,0.000003519007,0.001727665,0.8900188,0.06956922,0.00006845747,0.00003601672,0.03795163],"study_design_scores_gemma":[0.004750839,0.001991265,0.03359327,0.0008154107,0.0002784042,0.00001417726,0.0004787529,0.906086,0.05067827,0.000574428,0.0001634994,0.0005756839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6795922,0.0001465943,0.3194894,0.00001975457,0.0005146781,0.0001394927,0.00001978519,0.00003631068,0.00004185265],"genre_scores_gemma":[0.9913557,0.000176576,0.00823239,0.00001057194,0.0001610217,0.000004537228,0.0000306304,0.00002636842,0.000002173332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3117636,"threshold_uncertainty_score":0.4546925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00354701194167817,"score_gpt":0.2079855815828306,"score_spread":0.2044385696411525,"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."}}