{"id":"W2129161092","doi":"10.4028/www.scientific.net/amr.779-780.491","title":"A Method for Determining Length of Freeway Work Zone Based on Classification of Service Level","year":2013,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"VisSim; Traffic flow (computer networking); Level of service; Work (physics); Traffic volume; Transport engineering; Service (business); Software; Computer science; Traffic simulation; Work zone; Volume (thermodynamics); Simulation; Engineering; Computer network; Microsimulation; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008032439,0.001011623,0.0006658004,0.00385791,0.001016214,0.001613703,0.001365059,0.0006495094,0.003755308],"category_scores_gemma":[0.002362057,0.0004698291,0.000631895,0.002208419,0.0005304284,0.001184575,0.0008264753,0.0005852543,0.001374927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001114293,"about_ca_system_score_gemma":0.00202634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009520768,"about_ca_topic_score_gemma":0.008650118,"domain_scores_codex":[0.9982579,0.0002193399,0.0001673434,0.000488247,0.0007450579,0.0001221451],"domain_scores_gemma":[0.9984614,0.0003680341,0.0001596203,0.00009461773,0.0008407858,0.00007561351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005354979,0.0001777084,0.05411091,0.0009430154,0.00008801147,0.0001841731,0.001149054,0.04253277,0.04372858,0.01969348,0.01218205,0.8246747],"study_design_scores_gemma":[0.0001945776,0.0005887403,0.07061654,0.0002653435,0.000216965,0.001121959,0.001594041,0.7681812,0.09105658,0.009421085,0.05612209,0.0006209305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03080685,0.0002712671,0.9610751,0.00005683688,0.00009321171,0.0002294076,0.0007349527,0.001989759,0.004742687],"genre_scores_gemma":[0.2550414,0.0003478412,0.7385479,0.00003162538,0.00003908835,0.0007166799,0.00155908,0.0001673377,0.003549139],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009520768,"threshold_uncertainty_score":0.01893073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2063187071596832,"score_gpt":0.4265205940411538,"score_spread":0.2202018868814706,"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."}}