{"id":"W1031546370","doi":"10.3141/2259-10","title":"Turn Pocket Blockage and Spillback Models","year":2011,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Traffic control and management","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Paul University","funders":"","keywords":"Queue; Intersection (aeronautics); Signal timing; Turn (biochemistry); Microsimulation; Sensitivity (control systems); Level of service; Computer science; Truck; Phaser; Simulation; Mathematical optimization; Transport engineering; Engineering; Real-time computing; Automotive engineering; Mathematics; Traffic signal","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":[0.0003592014,0.000451884,0.0006345599,0.0005208242,0.0004181273,0.0009319609,0.001135788,0.0005530619,0.004966197],"category_scores_gemma":[0.001348559,0.000331141,0.0005378595,0.0005349983,0.0007683976,0.001236582,0.001149676,0.0008256342,0.0003915796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001397263,"about_ca_system_score_gemma":0.001310161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01880853,"about_ca_topic_score_gemma":0.01012991,"domain_scores_codex":[0.9995905,0.00007003012,0.00001522423,0.00005957617,0.0001421199,0.0001225484],"domain_scores_gemma":[0.9994936,0.0001837614,0.0001054203,0.00006932552,0.00008156001,0.00006623546],"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":[0.00003615514,0.00001507808,0.0005150374,0.00001068553,0.000004101408,0.00005019419,0.00002845129,0.9889941,0.001090555,0.007290326,0.0001362329,0.001829044],"study_design_scores_gemma":[0.000005650994,0.00002909838,0.0002665588,0.000003496916,0.000005029233,0.00001691525,0.00002114533,0.9961338,0.0006040332,0.002230772,0.0006777957,0.000005805342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3698196,0.0004732355,0.5948106,0.0002930623,0.00007507416,0.0001436003,0.0006553114,0.0008326778,0.03289684],"genre_scores_gemma":[0.9786214,0.0003017662,0.00908616,0.00003164924,0.00001114346,0.00008186237,0.0002146434,0.00005878532,0.01159251],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01880853,"threshold_uncertainty_score":0.03739816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09375421791256369,"score_gpt":0.3092647331127,"score_spread":0.2155105152001363,"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."}}