{"id":"W35926098","doi":"10.1021/acs.molpharmaceut.2c00457","title":"Traffic Signal Timing and Optimization","year":2012,"lang":"en","type":"article","venue":"Transportation research circular","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Canadian Institutes of Health Research; Amgen Canada; Terry Fox Foundation","keywords":"Reinforcement learning; Artificial neural network; Control (management); Traffic signal; SIGNAL (programming language); Computer science; Artificial intelligence; Range (aeronautics); Fuzzy logic; Fuzzy control system; Control engineering; Engineering; Machine learning; Real-time computing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0004070767,0.00007218095,0.0000763588,0.000135366,0.00007679383,0.00002656123,0.00005058448,0.00003964958,0.0001679302],"category_scores_gemma":[0.000003848834,0.00007689393,0.00002401964,0.0001852109,0.00003134897,0.0002098476,0.000001563085,0.0001284565,0.0000175915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002811788,"about_ca_system_score_gemma":0.000007159319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009363862,"about_ca_topic_score_gemma":0.0000138673,"domain_scores_codex":[0.9991373,0.00002749577,0.0001265242,0.00009779518,0.0002887032,0.0003221734],"domain_scores_gemma":[0.9997148,0.00003405813,0.000006993142,0.00008082273,0.0000425776,0.0001207453],"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":[0.000003911395,0.00002070888,0.0003234305,0.00009268609,0.00002800965,0.00000400715,0.0008367337,0.9777069,0.0005986582,0.0007157095,0.0001901807,0.01947908],"study_design_scores_gemma":[0.001147618,0.00004401507,0.1089378,0.00004049491,0.000056289,0.000001821955,0.000740015,0.8674096,0.0002555755,0.0000369835,0.02099068,0.0003390655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8087019,0.002441555,0.1864608,0.0001313877,0.0001338092,0.0004905878,0.000009128864,0.0004403693,0.001190466],"genre_scores_gemma":[0.9984342,0.0001604961,0.001200222,0.0000103189,0.00006251478,0.00004053151,0.00003955254,0.00001914065,0.00003296134],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1897323,"threshold_uncertainty_score":0.3135643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03528280440299841,"score_gpt":0.2751892654802742,"score_spread":0.2399064610772758,"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."}}