{"id":"W4390443434","doi":"10.18245/ijaet.1285587","title":"A benchmarking analysis on electric vehicle emissions of leading countries in electricity generation by energy sources","year":2023,"lang":"en","type":"article","venue":"International Journal of Automotive Engineering and Technologies","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electricity; Gasoline; Environmental science; Benchmarking; NOx; Combustion; Particulates; Electric vehicle; Sulfur dioxide; Waste management; Automotive engineering; Environmental economics; Business; Chemistry; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001738505,0.00009787703,0.0002014147,0.001422759,0.0000260663,0.00002554761,0.0001664179,0.00007954722,0.000003857296],"category_scores_gemma":[0.0001242157,0.00008704174,0.00005590739,0.001025541,0.00001663968,0.0001179239,0.00002495358,0.0001997578,4.135944e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007793237,"about_ca_system_score_gemma":0.00001223176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007195475,"about_ca_topic_score_gemma":0.000001984535,"domain_scores_codex":[0.9992915,0.000006980381,0.0002817069,0.00008064297,0.000203425,0.0001357449],"domain_scores_gemma":[0.9996222,0.0001141804,0.00008609865,0.0000540876,0.0001036014,0.00001987971],"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":[0.00001078185,0.00002229678,0.01047775,0.00001606031,0.0003994271,0.00001905904,0.0001962211,0.8478218,0.1146569,0.0004861416,0.0005669127,0.02532666],"study_design_scores_gemma":[0.0001506764,0.00007573736,0.005658309,0.00008592292,0.00002188001,0.000007219537,0.00006304962,0.7823943,0.2106412,0.00006563169,0.0007480155,0.00008807649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922024,0.0009775315,0.00628631,0.0001559602,0.0001331522,0.00001616724,0.00000694971,0.000179626,0.00004190382],"genre_scores_gemma":[0.9973373,0.002422439,0.0001607756,0.000004384389,0.00003996832,0.000002435756,0.00000466315,0.000008587625,0.00001949226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09598429,"threshold_uncertainty_score":0.3549459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00627611038947146,"score_gpt":0.2210580236756629,"score_spread":0.2147819132861915,"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."}}