{"id":"W2577496620","doi":"10.1155/2017/2130385","title":"Operational Efficiency Evaluation of Intersections with Dynamic Lane Assignment Using Field Data","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Variable (mathematics); Traffic flow (computer networking); Intersection (aeronautics); Transport engineering; Saturation (graph theory); Computer science; Statistics; Simulation; Mathematics; Engineering; Computer security","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":[0.003038404,0.0006778409,0.0004878383,0.002388986,0.0004474585,0.0007989644,0.0007407703,0.0003939737,0.0006470223],"category_scores_gemma":[0.006274343,0.0002072905,0.0004439417,0.00174292,0.0004280005,0.001453229,0.0007227437,0.0003301439,0.0001776982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001085068,"about_ca_system_score_gemma":0.001070715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01025887,"about_ca_topic_score_gemma":0.008822719,"domain_scores_codex":[0.9970787,0.001009185,0.0002499217,0.0005038416,0.0007699445,0.0003883698],"domain_scores_gemma":[0.9952974,0.001470841,0.001004338,0.0004305324,0.001567301,0.0002295737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006934323,0.0006504419,0.7960663,0.0001821873,0.0002235226,0.0001679429,0.0008733497,0.09753965,0.006489351,0.0008537631,0.0007793054,0.09548072],"study_design_scores_gemma":[0.00005702742,0.00194595,0.6610367,0.00004507972,0.0002017274,0.0001111383,0.003250661,0.3216324,0.008905753,0.0008067724,0.001895685,0.0001113266],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926482,0.00006034413,0.006215483,0.00002186472,0.000005924453,0.00004401062,0.0002122321,0.00005636381,0.0007355389],"genre_scores_gemma":[0.996849,0.00003399956,0.00245013,0.000003760959,0.000003870359,0.00003537293,0.0004487251,0.000003765187,0.0001714128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01025887,"threshold_uncertainty_score":0.02039832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02457696700688876,"score_gpt":0.2957953011660138,"score_spread":0.2712183341591251,"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."}}