{"id":"W2008440280","doi":"10.1002/atr.5670340206","title":"Evaluation of forced flows on freeways with single‐loop detectors","year":2000,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Washington State University; U.S. Department of Transportation","keywords":"Bottleneck; Computer science; Metering mode; Traffic congestion; Traffic flow (computer networking); Real-time computing; Operations research; Transport engineering; Simulation; Engineering; Computer network","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":[0.0002437797,0.00008552102,0.0001287885,0.0001393766,0.00001563298,0.000004727516,0.00005677684,0.00003386737,0.0000616402],"category_scores_gemma":[0.000005928919,0.00007325734,0.0000525493,0.0001420653,0.00001029186,0.0002749694,1.82549e-7,0.00009078732,9.646601e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006529881,"about_ca_system_score_gemma":0.00001391074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.923333e-7,"about_ca_topic_score_gemma":0.00005075672,"domain_scores_codex":[0.9990088,0.00001594667,0.00032764,0.00005752868,0.0005144691,0.00007557749],"domain_scores_gemma":[0.9995846,0.00001313995,0.0001090385,0.0000747735,0.0001850312,0.00003347524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008484237,0.00003156503,0.00002290326,0.00001863567,0.00004223151,0.000001977431,0.0002431317,0.7522562,0.0158268,0.00002742422,0.0000577879,0.2313865],"study_design_scores_gemma":[0.01639112,0.007276332,0.1873699,0.001761938,0.002279876,0.00002957243,0.001355346,0.2060182,0.5670487,0.001277387,0.008155231,0.001036459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.966303,0.00007031525,0.03179828,0.00001174377,0.0001278717,0.0001702432,0.000004467025,0.000223551,0.001290555],"genre_scores_gemma":[0.9951798,0.0001159056,0.004627989,0.000008929101,0.0000297534,0.000006261253,0.000007628029,0.00001595717,0.000007814929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5512219,"threshold_uncertainty_score":0.2987348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01148932307158632,"score_gpt":0.2235105653163909,"score_spread":0.2120212422448046,"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."}}