{"id":"W4390681935","doi":"10.1049/icp.2023.3140","title":"Designing EV charging stations deployment through holistic simulations: the SANEVEC project","year":2023,"lang":"en","type":"article","venue":"IET conference proceedings.","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Grid; Software deployment; Charging station; Electricity; Computer science; Air quality index; Quality (philosophy); Electric vehicle; Transport engineering; Task (project management); Environmental science; Simulation; Automotive engineering; Engineering; Systems engineering; Electrical engineering; Meteorology; Power (physics); Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.0001363076,0.0001869822,0.0001456796,0.0001000457,0.0002987598,0.0002321134,0.0002342404,0.00007140148,0.00005827445],"category_scores_gemma":[0.00009504393,0.0001439394,0.0000385994,0.0009127536,0.00004003499,0.0003692102,0.00002755616,0.0002897151,0.00004686308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007357311,"about_ca_system_score_gemma":0.00006763729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002512899,"about_ca_topic_score_gemma":0.000005765691,"domain_scores_codex":[0.9989024,0.000007131131,0.0002340719,0.000208282,0.0002371502,0.0004109124],"domain_scores_gemma":[0.9995702,0.00007616629,0.00005091283,0.00009944435,0.0001655357,0.00003775522],"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":[0.00005379818,0.00009036026,0.01914352,0.001417094,0.0006771606,0.00002893764,0.1116387,0.1887929,0.3037459,0.1558961,0.1561441,0.06237146],"study_design_scores_gemma":[0.0004423849,0.00007993648,0.006034317,0.0001868673,0.0000717349,0.00001806838,0.004537239,0.942023,0.01693226,0.0171925,0.01191796,0.0005636961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.900824,0.0005061732,0.07673425,0.001313613,0.0006747713,0.001916547,0.00007851355,0.003976161,0.01397604],"genre_scores_gemma":[0.997201,0.0001545937,0.002096743,0.00009776505,0.0001427553,0.00009590007,0.00002158397,0.00004031027,0.0001493679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7532302,"threshold_uncertainty_score":0.5869676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05639596175104149,"score_gpt":0.2896665641967774,"score_spread":0.2332706024457359,"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."}}