{"id":"W2810120777","doi":"10.1155/2018/1645475","title":"Design of Signal Timing Plan for Urban Signalized Networks including Left Turn Prohibition","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Signal timing; Intersection (aeronautics); SIGNAL (programming language); Plan (archaeology); Turn (biochemistry); Computer science; Travel time; Sequence (biology); Transport engineering; Simulation; Mathematical optimization; Real-time computing; Traffic signal; Engineering; Mathematics; Geography","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":[0.0009060346,0.0001084163,0.0002393692,0.0001732981,0.0003143478,0.00002289057,0.0001135656,0.0001061747,0.0000482075],"category_scores_gemma":[0.00005968222,0.0001079358,0.000103211,0.0002270884,0.0001180998,0.0006735567,5.113367e-7,0.0001146173,3.971325e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005124242,"about_ca_system_score_gemma":0.0001782522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001697236,"about_ca_topic_score_gemma":0.0001727052,"domain_scores_codex":[0.9984962,0.0000960292,0.0007059945,0.0001253969,0.0003758005,0.0002005604],"domain_scores_gemma":[0.9978263,0.0002560267,0.0009321134,0.00004830092,0.0008525942,0.00008465916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001959357,0.00007420225,0.003126505,0.00004437436,0.00005253856,0.000004447633,0.04002181,0.9401952,0.01015579,0.001009106,0.0001912391,0.003165393],"study_design_scores_gemma":[0.05637307,0.02008149,0.3788671,0.01000824,0.004184579,0.00005064258,0.09126284,0.1981385,0.1532434,0.0478164,0.03478441,0.005189311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1118587,0.000101708,0.8871378,0.000101818,0.0003344809,0.0003663221,0.00001265712,0.00002682471,0.00005963794],"genre_scores_gemma":[0.9382166,0.0000701528,0.06112147,0.00003624958,0.000429281,0.000005376021,0.00007451947,0.00001616725,0.00003021831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8263578,"threshold_uncertainty_score":0.4401496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04479607134893407,"score_gpt":0.3153381176795994,"score_spread":0.2705420463306653,"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."}}