{"id":"W2606917679","doi":"10.1155/2017/4390630","title":"Variable Speed Limit Signs: Control and Setting Locations in Freeway Work Zones","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Speed limit; Queue; Variable (mathematics); Computer science; Limit (mathematics); Work (physics); Set (abstract data type); Control limits; Time limit; Control variable; Control theory (sociology); Simulation; Control (management); Transport engineering; Engineering; Mathematics; Artificial intelligence; Machine learning","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":[0.001468947,0.0009076963,0.0008286685,0.0008523855,0.0007759694,0.002372559,0.002028469,0.001211387,0.001489927],"category_scores_gemma":[0.003977459,0.0006298441,0.0005498651,0.0008340548,0.0009579891,0.002701361,0.001557521,0.001002987,0.0002553122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001087871,"about_ca_system_score_gemma":0.001759656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007374707,"about_ca_topic_score_gemma":0.005620759,"domain_scores_codex":[0.9985896,0.0005558647,0.00006848761,0.0002919518,0.0002190285,0.0002751491],"domain_scores_gemma":[0.9982009,0.0006924374,0.0004315304,0.0001185574,0.0003207805,0.0002357716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003022821,0.000138598,0.003900608,0.0001172622,0.0000253794,0.0001838927,0.0003487069,0.927053,0.003794998,0.01106705,0.000491238,0.05257705],"study_design_scores_gemma":[0.00002734947,0.0001250637,0.0006601051,0.00001647467,0.00002163264,0.00003372018,0.0002351036,0.9919613,0.002146783,0.004011782,0.0007331369,0.00002757336],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2355667,0.0002767232,0.7589663,0.0003056465,0.00005987094,0.0001407819,0.0001073259,0.0005001505,0.004076568],"genre_scores_gemma":[0.9809939,0.00005557842,0.01815835,0.00001396958,0.000006629362,0.00004771825,0.00002582779,0.00001317823,0.00068499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007374707,"threshold_uncertainty_score":0.01466358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005523681967385998,"score_gpt":0.2051427244639683,"score_spread":0.1996190424965822,"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."}}