{"id":"W4309672183","doi":"10.1155/2022/9277000","title":"Analysis on Lane Capacity for Expressway Toll Station Using Toll Data","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Toll; Transport engineering; Electronic toll collection; Toll road; Reliability (semiconductor); Engineering; Computer science","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":[0.0002196352,0.00007361364,0.000154242,0.0002940358,0.0000709234,0.00001056841,0.0001512035,0.00001734394,0.00001792497],"category_scores_gemma":[0.000006691929,0.00007851241,0.00007761216,0.0002359509,0.000005538217,0.000404048,0.000002713394,0.0001244035,1.135584e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007877946,"about_ca_system_score_gemma":0.000008964717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004199829,"about_ca_topic_score_gemma":0.00003728786,"domain_scores_codex":[0.9992477,0.00001594693,0.0003263117,0.00009606839,0.0002288218,0.00008512093],"domain_scores_gemma":[0.9995832,0.00002974938,0.0001571131,0.0001515339,0.00004670653,0.00003165837],"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":[0.0000747879,0.00003420518,0.0001336264,0.00002875024,0.0001856051,0.000003647401,0.0002764122,0.9856274,0.003508556,0.0001886255,0.0008363157,0.009102033],"study_design_scores_gemma":[0.004824132,0.001125321,0.06539978,0.00009679054,0.003300886,0.00001218606,0.002696137,0.7435419,0.008876802,0.0008721175,0.1685046,0.0007493534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3013102,0.00004295897,0.6974437,0.00002730578,0.0002988444,0.0001423377,0.0005149413,0.0001812718,0.0000385419],"genre_scores_gemma":[0.9488056,0.00005100329,0.05053959,0.00003028827,0.00004210755,0.00001028393,0.000502017,0.00001276191,0.000006370859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6474954,"threshold_uncertainty_score":0.3201643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03287611920757446,"score_gpt":0.2727938840405296,"score_spread":0.2399177648329552,"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."}}