{"id":"W2713203437","doi":"10.1016/j.trd.2017.06.019","title":"Life cycle GHG emissions and lifetime costs of medium-duty diesel and battery electric trucks in Toronto, Canada","year":2017,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":95,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"AUTO21 Network of Centres of Excellence","keywords":"Truck; Diesel fuel; Greenhouse gas; Automotive engineering; Environmental science; Battery (electricity); Fuel efficiency; Life-cycle assessment; Waste management; Environmental engineering; Engineering; Production (economics); Power (physics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002298468,0.000348247,0.0002279772,0.001001124,0.001231033,0.0009819532,0.000800508,0.0003259603,0.003236286],"category_scores_gemma":[0.000546565,0.0002765798,0.0006644634,0.001923359,0.0004362275,0.0004413289,0.0003493463,0.0003552042,0.0002046235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05025716,"about_ca_system_score_gemma":0.01770623,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9971815,"about_ca_topic_score_gemma":0.9984107,"domain_scores_codex":[0.9997247,0.00001425977,0.00001328366,0.0000309539,0.0001170764,0.00009980041],"domain_scores_gemma":[0.9994822,0.00004166373,0.00004678995,0.00001050184,0.0003346535,0.00008408155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001704856,0.0001615208,0.8347074,0.0004708504,0.000496046,0.001442544,0.001599276,0.09993926,0.006917776,0.007864824,0.01523622,0.02945933],"study_design_scores_gemma":[0.00002408526,0.00006230569,0.96709,0.00006015435,0.0001062593,0.0001126247,0.002832004,0.01972622,0.001351394,0.0003615848,0.008219361,0.00005398468],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9801055,0.0009191327,0.0002652948,0.0002025734,0.000007437409,0.00002828019,0.01176174,0.00002297969,0.00668704],"genre_scores_gemma":[0.9878853,0.0004514656,0.0001561287,0.00002237914,0.000001410406,0.000005453047,0.003924027,0.000006502481,0.007547277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05025716,"threshold_uncertainty_score":0.3646429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01023389469378298,"score_gpt":0.241979353066899,"score_spread":0.231745458373116,"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."}}