{"id":"W2601367636","doi":"10.1139/cjce-2016-0259","title":"Impact of using indirect left-turns on signalized intersections’ performance","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Intersection (aeronautics); Turn (biochemistry); Transport engineering; Signal timing; Control (management); SIGNAL (programming language); Computer science; Simulation; Engineering; Physics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001521376,0.0001239314,0.0001996888,0.0005793586,0.00007150202,0.00005908713,0.0002542837,0.0000535865,0.00007194038],"category_scores_gemma":[0.00005098778,0.0001217163,0.0001373168,0.00005829371,0.00002534076,0.0002921831,0.000007645634,0.0002322578,0.000001152941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002824075,"about_ca_system_score_gemma":0.0001041288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004271592,"about_ca_topic_score_gemma":0.006895631,"domain_scores_codex":[0.999398,0.000005303416,0.0002480344,0.00005312224,0.00009506821,0.0002004493],"domain_scores_gemma":[0.9994112,0.00001168201,0.0001110641,0.0001889615,0.00005352971,0.0002235718],"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":[0.00001061485,0.000005694277,0.008927037,0.00008651605,0.0002167734,0.00002919196,0.0003375618,0.983187,0.003298433,0.00002978833,0.002003942,0.001867495],"study_design_scores_gemma":[0.001141665,0.0005949297,0.2849558,0.001635541,0.0001177656,0.0003016739,0.00006346119,0.6999415,0.005564359,0.00001900118,0.005115155,0.0005491842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725715,0.0001444038,0.02187418,0.000006485027,0.0009076687,0.00006553395,0.000008744743,0.0001615877,0.004259913],"genre_scores_gemma":[0.9996057,0.00005334324,0.0001984537,0.000003437996,0.0001018562,4.307195e-7,5.006602e-7,0.00002620085,0.00001005786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2832454,"threshold_uncertainty_score":0.4963447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01595647078488357,"score_gpt":0.2290954656802028,"score_spread":0.2131389948953193,"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."}}