{"id":"W2983422723","doi":"10.1139/cjce-2018-0601","title":"Modeling arterial signal coordination for bus priority using mobile phone GPS data","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Global Positioning System; VisSim; Real-time computing; Mobile phone; Mobile phone tracking; Computer science; SIGNAL (programming language); Assisted GPS; Software; Simulation; Embedded system; Mobile station; Engineering; Telecommunications; GSM services; Base station; Transport engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002130892,0.0004999943,0.0002897523,0.0007372111,0.0004205319,0.0007393651,0.0006356481,0.0006076391,0.001841321],"category_scores_gemma":[0.0006545843,0.0003401324,0.0003909522,0.0006670242,0.0002961838,0.0006844045,0.0003276736,0.000335651,0.0003158317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001206339,"about_ca_system_score_gemma":0.001670779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05403822,"about_ca_topic_score_gemma":0.03758123,"domain_scores_codex":[0.9998006,0.00003406945,0.000009215604,0.00005742564,0.00004692477,0.00005174554],"domain_scores_gemma":[0.9998024,0.0000512742,0.000037227,0.00001090404,0.00008149866,0.00001670598],"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":[0.00002110442,0.00001778316,0.003293812,0.00001288093,0.00000599654,0.00005882898,0.00004136074,0.9890431,0.001555519,0.001729274,0.0001914083,0.004028914],"study_design_scores_gemma":[0.000002547467,0.000008756904,0.0005570267,0.000001234365,0.000005485223,0.000006260499,0.00001377552,0.9987687,0.0003067447,0.0001711191,0.0001553392,0.000002915387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.488597,0.0001737646,0.49164,0.0002657034,0.00004370534,0.0001583021,0.0006140247,0.0008849362,0.01762261],"genre_scores_gemma":[0.9871457,0.00009399227,0.009586548,0.000009331575,0.000006391394,0.00005171111,0.0001347528,0.00002305373,0.002948687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05403822,"threshold_uncertainty_score":0.1074474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01732665173485102,"score_gpt":0.2147774333966627,"score_spread":0.1974507816618117,"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."}}