{"id":"W3196449209","doi":"10.3390/wevj12030151","title":"Fuel Selections for Electrified Vehicles: A Well-to-Wheel Analysis","year":2021,"lang":"en","type":"article","venue":"World Electric Vehicle Journal","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China","keywords":"Greenhouse gas; Green vehicle; Electricity; Miles per gallon gasoline equivalent; Battery electric vehicle; Gasoline; Environmental science; Work (physics); Sustainability; Alternative fuel vehicle; Automotive engineering; Sustainable transport; Electric vehicle; Environmental economics; Fuel efficiency; Alternative fuels; Engineering; Diesel fuel; Waste management; Economics; Electrical 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004198576,0.0004152361,0.0006557491,0.001666428,0.0005243779,0.000355318,0.0003998597,0.0001796106,0.0004014095],"category_scores_gemma":[0.0001023628,0.000429902,0.0006357148,0.01269632,0.00001517325,0.0002591964,0.00002696401,0.001187548,0.00006781666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005240978,"about_ca_system_score_gemma":0.0003037473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009847727,"about_ca_topic_score_gemma":0.0002422098,"domain_scores_codex":[0.9969385,0.00009132131,0.0007581965,0.0004636081,0.0004647044,0.001283722],"domain_scores_gemma":[0.998215,0.0002035375,0.0001265028,0.0003999903,0.0005136055,0.0005414201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002101423,0.0002797987,0.007150671,0.0001472335,0.005797738,0.0001570323,0.0004974535,0.1566442,0.505481,0.001897058,0.2260619,0.09567576],"study_design_scores_gemma":[0.003306258,0.0006490659,0.02950171,0.00005883559,0.002751928,0.001125588,0.0001177051,0.4981804,0.1622328,0.00687047,0.2932658,0.001939455],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7179497,0.01542858,0.2364708,0.004430363,0.001694631,0.001298837,0.000051776,0.001497478,0.02117781],"genre_scores_gemma":[0.9885255,0.0005572924,0.004418826,0.000948835,0.0009816771,0.00006064629,0.00002286548,0.000112161,0.004372264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3432482,"threshold_uncertainty_score":0.9998153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005976636185861627,"score_gpt":0.2181386837450795,"score_spread":0.2121620475592179,"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."}}