{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002243479,0.0002250671,0.0003533184,0.0007189416,0.0002834828,0.0000809181,0.0007008997,0.0001323279,0.0003432499],"category_scores_gemma":[0.00003852092,0.000170215,0.0002263686,0.0009404161,0.0003581854,0.0006134722,0.000007010061,0.00145042,0.00001588492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001052916,"about_ca_system_score_gemma":0.0001341577,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002349075,"about_ca_topic_score_gemma":0.02068777,"domain_scores_codex":[0.9958419,0.0003284631,0.0009211535,0.0002694409,0.001877724,0.0007613411],"domain_scores_gemma":[0.9977437,0.0003262795,0.0001314843,0.0003668964,0.001057243,0.0003743662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.008750928,0.002267277,0.2051835,0.005668602,0.003971773,0.002281236,0.08991919,0.1417376,0.02297984,0.09813742,0.1052235,0.3138791],"study_design_scores_gemma":[0.002189253,0.0005102913,0.9648817,0.0003094413,0.00009305608,0.000001210905,0.002373194,0.003033537,0.0009906384,0.01248524,0.01282148,0.0003109204],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922647,0.0009277678,0.003120607,0.0005934887,0.0004687464,0.0007390585,0.00003901194,0.00007806611,0.001768548],"genre_scores_gemma":[0.9946029,0.002975321,0.001713935,0.00003226752,0.0001076056,0.00004512151,0.000004729588,0.00005561679,0.0004625612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7596982,"threshold_uncertainty_score":0.9971821,"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."}}