{"id":"W2573015345","doi":"","title":"Will fleet managers really help vehicle fleets to become electric?","year":2016,"lang":"en","type":"preprint","venue":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fleet management; Business; Electricity; De facto; Quarter (Canadian coin); Transport engineering; Operations research; Computer science; Telecommunications; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009381154,0.0005032657,0.001069444,0.001492355,0.0007374759,0.00002422522,0.003804811,0.0009071066,0.0008153553],"category_scores_gemma":[0.00005086896,0.0005960601,0.0006199136,0.001611383,0.0009197696,0.0004866685,0.002556571,0.002171052,0.00003969371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006725214,"about_ca_system_score_gemma":0.0004534253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004744709,"about_ca_topic_score_gemma":0.003316225,"domain_scores_codex":[0.9962573,0.0003987477,0.0003063517,0.000790152,0.001237761,0.001009707],"domain_scores_gemma":[0.9964576,0.0004016758,0.0003435927,0.001362239,0.0009575548,0.0004773268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01038615,0.002601547,0.01024065,0.009330302,0.01011592,0.002227352,0.08473384,0.168042,0.09275142,0.008863085,0.3463463,0.2543614],"study_design_scores_gemma":[0.0212198,0.006447742,0.1051732,0.008792674,0.003331495,0.00009100833,0.2123193,0.116316,0.005508789,0.008874246,0.5039777,0.007948041],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9495674,0.0008437127,0.01664918,0.01000152,0.0002923307,0.001548466,0.001250344,0.000336445,0.01951058],"genre_scores_gemma":[0.9832683,0.004515162,0.004073428,0.00002893669,0.0001117397,3.53413e-8,0.0001143284,0.00005823487,0.007829862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2464134,"threshold_uncertainty_score":0.9996491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01785548251645913,"score_gpt":0.2284455676045131,"score_spread":0.210590085088054,"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."}}