{"id":"W4220824503","doi":"10.1016/j.trd.2022.103233","title":"Energy and greenhouse gas implications of shared automated electric vehicles","year":2022,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Greenhouse gas; Electrification; Relocation; Electricity; Electric vehicle; Environmental science; Automotive engineering; Environmental economics; Transport engineering; Engineering; Computer science; Electrical engineering; Power (physics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004673138,0.0004246724,0.0002331703,0.0006670859,0.0006366595,0.001274367,0.0006281365,0.0009482977,0.00483139],"category_scores_gemma":[0.001252898,0.0001573291,0.0005879006,0.0009949048,0.0008316098,0.002073233,0.001031906,0.0005246891,0.0002362599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002221395,"about_ca_system_score_gemma":0.0008384706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0192605,"about_ca_topic_score_gemma":0.02448399,"domain_scores_codex":[0.9994928,0.0001487118,0.00001351366,0.00007340559,0.0001151627,0.0001563883],"domain_scores_gemma":[0.9989772,0.0004857077,0.0001035065,0.00005729327,0.0003347167,0.00004162775],"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":[0.007053842,0.0011522,0.2444357,0.0005750924,0.0008017446,0.004293822,0.001790375,0.5083441,0.0477074,0.07831696,0.005035301,0.1004936],"study_design_scores_gemma":[0.0003237354,0.00224376,0.4271558,0.00018167,0.001172489,0.001009381,0.03613075,0.2555879,0.08520558,0.1631769,0.02750579,0.0003062146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904558,0.0003453382,0.000845468,0.0004032918,0.00004478644,0.000007865383,0.0002194751,0.00000905611,0.007668944],"genre_scores_gemma":[0.9991888,0.00008580446,0.00005214886,0.000009664718,0.00000647422,0.000001720104,0.00004745043,0.00000218358,0.0006058446],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0192605,"threshold_uncertainty_score":0.03829676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0295796858312935,"score_gpt":0.2638574108468564,"score_spread":0.2342777250155629,"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."}}