{"id":"W4367360147","doi":"10.5220/0011792500003479","title":"Optimizing CAV Driving Behaviour to Reduce Traffic Congestion and GHG Emissions","year":2023,"lang":"en","type":"article","venue":"","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Greenhouse gas; Computer science; Traffic congestion; Environmental science; Transport engineering; Automotive engineering; Business; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009352471,0.00009068525,0.00008475893,0.0001030571,0.0001214507,0.00003607863,0.00005744721,0.00005496354,0.00009836867],"category_scores_gemma":[0.00001765953,0.00008358471,0.00001700184,0.0002865049,0.000007863496,0.00009506282,0.00003481,0.0001094765,0.00006863851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002089952,"about_ca_system_score_gemma":0.000008277426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006548829,"about_ca_topic_score_gemma":0.00000904218,"domain_scores_codex":[0.9994736,0.000005391553,0.0001141157,0.0001260229,0.00007328045,0.0002076066],"domain_scores_gemma":[0.9996526,0.00002827525,0.000006570811,0.0001151321,0.00001392544,0.0001834807],"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":[0.000003258392,0.00001017103,0.002639861,0.00003871434,0.0000103115,0.00001264643,0.0015963,0.8404824,0.06030906,0.00004668684,0.01679765,0.07805298],"study_design_scores_gemma":[0.0003060407,0.00004301511,0.07374715,0.0002441803,0.00001725548,0.00002785659,0.0008040009,0.9057149,0.009725405,0.000006110741,0.008952651,0.0004114697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964644,0.00005469688,0.0003607729,0.0003266298,0.0001823515,0.00008612039,0.00000224528,0.0007416171,0.001781147],"genre_scores_gemma":[0.9953505,0.0001217127,0.002469138,0.00001907776,0.00005415544,0.00001481629,0.000005646283,0.00002220279,0.001942756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07764151,"threshold_uncertainty_score":0.3408485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01739270741946293,"score_gpt":0.2553266645956087,"score_spread":0.2379339571761457,"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."}}