{"id":"W4413915964","doi":"10.1016/j.cstp.2025.101588","title":"Addressing the electric vehicle adoption gap for small fleets: A case study of local energy transitions in British Columbia","year":2025,"lang":"en","type":"article","venue":"Case Studies on Transport Policy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Pacific Institute for Climate Solutions; U.S. Department of Energy","keywords":"Electric vehicle; Business; Energy (signal processing); Transport engineering; Engineering; Physics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001314879,0.0001541788,0.000347093,0.000181828,0.0002996738,0.00002972553,0.00008711105,0.00008951808,0.000003139843],"category_scores_gemma":[0.00001299221,0.0001846694,0.0001052094,0.001070695,0.00006672485,0.00005459501,0.000005282937,0.0002189354,1.099838e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001683513,"about_ca_system_score_gemma":0.00007112762,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02143703,"about_ca_topic_score_gemma":0.4191501,"domain_scores_codex":[0.9988445,0.00003839226,0.0004671826,0.0002238265,0.00008927117,0.0003368134],"domain_scores_gemma":[0.9995386,0.00009431635,0.00004221433,0.0001907152,0.00009271356,0.00004141693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002239153,0.001797101,0.005495587,0.00205514,0.002215277,0.0395162,0.0285224,0.2693829,0.002171912,0.002177907,0.003030163,0.6434115],"study_design_scores_gemma":[0.04624373,0.01058342,0.08488563,0.003990551,0.004392429,0.05260769,0.4473808,0.3241335,0.008140685,0.007767817,0.004745911,0.005127802],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953769,0.001608222,0.001960953,0.00008968182,0.00008642116,0.0005368902,0.00005922051,0.00008074565,0.0002008927],"genre_scores_gemma":[0.999207,0.0001932664,0.00003230709,0.0001713807,0.00008219718,0.0002294531,0.000007669719,0.00002742943,0.00004936077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6382837,"threshold_uncertainty_score":0.9850793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03174549265519627,"score_gpt":0.2805734731440417,"score_spread":0.2488279804888454,"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."}}