{"id":"W4302012080","doi":"10.32920/ryerson.14661255.v1","title":"Air quality improvement in urban areas using traffic operation management","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Pollutant; Particulates; Air quality index; Environmental science; Air pollution; Public transport; Air pollutants; Criteria air contaminants; Pollution; Business; Environmental planning; Transport engineering; Environmental engineering; Environmental protection; Natural resource economics; Engineering; Meteorology; Geography; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003348868,0.0001987174,0.0002009362,0.0001429948,0.00006917572,0.0000370869,0.0001920103,0.00009301786,0.0009384715],"category_scores_gemma":[9.631329e-7,0.0002033486,0.00006064248,0.0001092653,0.000006218617,0.00006499243,0.0003556251,0.0004450525,0.000006752803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00048404,"about_ca_system_score_gemma":0.00002398986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001454803,"about_ca_topic_score_gemma":0.00006138118,"domain_scores_codex":[0.9988812,0.00002777178,0.0003975216,0.000275645,0.0002067888,0.0002110836],"domain_scores_gemma":[0.9995195,0.000006781594,0.00003477267,0.000379228,0.000009637249,0.00005005127],"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":[0.00000418736,0.00003525086,0.0004427037,0.0004075859,0.00002723524,0.000004624369,0.0002646392,0.9738027,0.0002872575,0.0001404166,0.0003848808,0.02419845],"study_design_scores_gemma":[0.0002740044,0.00001401087,0.005961603,0.00007768472,0.00001162206,5.671977e-7,0.0003409674,0.9854329,0.0003644801,0.00002438583,0.007156111,0.0003416574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853896,0.0001776704,0.002599708,0.00004208404,0.0006381656,0.0005017151,0.00001563867,0.0002227531,0.01041268],"genre_scores_gemma":[0.9965615,0.0001645125,0.002100604,0.00005469519,0.00006945358,0.0001226348,0.00008565827,0.00002970239,0.0008112194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02385679,"threshold_uncertainty_score":0.9999748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02719132975759621,"score_gpt":0.2801566569527538,"score_spread":0.2529653271951576,"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."}}