{"id":"W3046814773","doi":"10.1155/2020/9401062","title":"Deployment Optimization of Connected and Automated Vehicle Lanes with the Safety Benefits on Roadway Networks","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Software deployment; Bilevel optimization; Scheme (mathematics); Genetic algorithm; Traffic flow (computer networking); Computer science; Transport engineering; Simulation; Engineering; Optimization problem; Computer network; Algorithm","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":[0.00004427596,0.00006725923,0.0001220347,0.00002390268,0.00002294963,0.000005817364,0.00003733548,0.00001797961,0.000004085723],"category_scores_gemma":[0.000002776378,0.00004423609,0.00002121426,0.0001052329,0.000009300816,0.00009493065,5.905599e-7,0.00006916799,9.706075e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009666467,"about_ca_system_score_gemma":0.000003740187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.481612e-7,"about_ca_topic_score_gemma":0.00002524223,"domain_scores_codex":[0.999555,0.000008845853,0.0002151601,0.00004746867,0.0001131419,0.00006039487],"domain_scores_gemma":[0.9997345,0.00003172894,0.0001084014,0.00003353543,0.00005681421,0.00003501397],"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":[0.000334504,0.00001078108,0.00009023696,0.00002600606,0.00006067477,0.000003937199,0.0005753698,0.986556,0.0004059162,0.00009692278,0.00002791189,0.01181173],"study_design_scores_gemma":[0.002223805,0.0004324858,0.2591409,0.00009037434,0.0001002278,0.000001411165,0.0003134283,0.7369839,0.000288192,0.000002143409,0.0003401429,0.00008303817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9209659,0.0006234886,0.07701381,0.0009383964,0.00008130204,0.0002058623,0.000006158861,0.0001336538,0.00003149515],"genre_scores_gemma":[0.9982365,0.0003279624,0.001320389,0.00006406174,0.00002761415,0.000001913664,0.000009909183,0.00001067181,0.000001007165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2590506,"threshold_uncertainty_score":0.1803895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004312835616413224,"score_gpt":0.1757205301071274,"score_spread":0.1714076944907142,"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."}}