{"id":"W4200582946","doi":"10.1016/j.scitotenv.2021.152323","title":"Comparative analysis of drive-cycles, speed limit violations, and emissions in two cities: Toronto and Beijing","year":2021,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada","keywords":"Beijing; Metropolitan area; Enforcement; Transport engineering; TRIPS architecture; Environmental science; Traffic congestion; Speed limit; Greenhouse gas; Meteorology; Geography; Engineering; China; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002025788,0.000057271,0.0001340149,0.00003244628,0.0001178593,0.00001035574,0.0001190763,0.00001007,0.00008493374],"category_scores_gemma":[0.000009046888,0.00003560037,0.00002720679,0.0002624815,0.0003252005,0.0001101856,0.00014859,0.00005397794,3.132307e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005543706,"about_ca_system_score_gemma":0.00001361262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007687087,"about_ca_topic_score_gemma":0.00003129921,"domain_scores_codex":[0.9994847,0.00001999745,0.0001406041,0.00009787716,0.0001596316,0.00009719676],"domain_scores_gemma":[0.9996666,0.00004734439,0.00003457759,0.0002089356,0.000005442507,0.00003709512],"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":[0.000002436735,0.00001778282,0.004115902,0.000007506622,0.00004310566,1.817122e-7,0.00386701,0.803595,0.1873825,0.0001623799,0.000005676889,0.0008004428],"study_design_scores_gemma":[0.0001018802,0.000008097723,0.3577596,0.00003828725,0.00005996237,0.000001861566,0.002138305,0.6160007,0.02377152,0.00004405041,0.00001921492,0.00005653695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977646,0.0007873615,0.00002411754,0.00008179617,0.00002255033,0.00005447979,0.000007264711,0.000003305054,0.001254557],"genre_scores_gemma":[0.9992366,0.0003444981,0.0002788584,0.000002547762,0.00000427775,0.000001262768,5.854201e-7,0.000001879252,0.0001294777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3536437,"threshold_uncertainty_score":0.1451741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01350298939317421,"score_gpt":0.2467784406415186,"score_spread":0.2332754512483444,"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."}}