{"id":"W3183423921","doi":"10.1155/2021/8863487","title":"Variable Speed Limit Control Method of Freeway Mainline in Intelligent Connected Environment","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Education of Hebei Province","keywords":"Bottleneck; Speed limit; Intelligent transportation system; Microsimulation; Limit (mathematics); Intelligent control; Variable (mathematics); Traffic congestion; Computer science; Transport engineering; Engineering; Automotive engineering; Simulation; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000263745,0.0004959662,0.0003369761,0.0003785798,0.0004239025,0.0006178601,0.000758691,0.0003735516,0.001298456],"category_scores_gemma":[0.0004128534,0.000174807,0.0004768328,0.000238657,0.0004282919,0.0006252952,0.0004256177,0.0003133953,0.0001409749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006256165,"about_ca_system_score_gemma":0.0005586843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008765674,"about_ca_topic_score_gemma":0.004653623,"domain_scores_codex":[0.9997666,0.00004136657,0.000009897187,0.00007800652,0.00007439723,0.00002974753],"domain_scores_gemma":[0.9998422,0.0000299966,0.00003834579,0.00001340945,0.00006213265,0.00001391867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001753734,0.00007335605,0.001704297,0.000161538,0.00005680671,0.000153644,0.0002032539,0.892777,0.02201286,0.01290923,0.001001106,0.06877165],"study_design_scores_gemma":[0.00001264265,0.00009107776,0.0002962743,0.000005233416,0.00001136826,0.00001706625,0.00001304512,0.9954385,0.002227395,0.001015175,0.0008651289,0.000007117751],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1046596,0.0003821982,0.8823753,0.0001775179,0.0000915216,0.00006715048,0.00005092638,0.000643492,0.01155233],"genre_scores_gemma":[0.9895505,0.00006911193,0.00867236,0.00001964626,0.000009999824,0.00003909083,0.00001980981,0.00001418503,0.001605198],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008765674,"threshold_uncertainty_score":0.01742929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005910338215207193,"score_gpt":0.2109638244500272,"score_spread":0.20505348623482,"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."}}