{"id":"W3165461565","doi":"10.1109/mim.2021.9436092","title":"An Overview of IoT-Enabled Monitoring and Control Systems for Electric Vehicles","year":2021,"lang":"en","type":"article","venue":"IEEE Instrumentation & Measurement Magazine","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Internet of Things; Pace; Smart city; Battery (electricity); Wireless sensor network; Computer science; Cloud computing; Efficient energy use; Electric vehicle; Smart grid; Computer security; Systems engineering; Telecommunications; Engineering; Computer network; Electrical engineering","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":[0.0004541269,0.000180356,0.0002748329,0.0001326529,0.00005620592,0.00007231039,0.00008909881,0.00004761589,0.000008663832],"category_scores_gemma":[0.00002476759,0.0002003551,0.00004815188,0.0002584443,0.00001129556,0.0001913062,0.000007623965,0.00005950395,0.000004411722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002098024,"about_ca_system_score_gemma":0.00003111902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001420969,"about_ca_topic_score_gemma":0.00001010075,"domain_scores_codex":[0.9985709,0.00006277791,0.0004284052,0.000226642,0.0004684988,0.0002427516],"domain_scores_gemma":[0.9992819,0.0000303985,0.00008762443,0.0002302771,0.0002916887,0.00007811348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002846364,0.00005984222,0.004738702,0.000761608,0.0001979959,0.000002703988,0.00005899193,0.1744491,0.812473,0.0002864689,0.0004251286,0.00651799],"study_design_scores_gemma":[0.005593705,0.0002633152,0.05061021,0.0004031782,0.0003257372,0.00001000921,0.0002374128,0.2434537,0.6930209,0.0001104261,0.005477741,0.000493695],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.963727,0.009291464,0.02364674,0.00007773039,0.001941258,0.0007689383,0.00001700741,0.0002143795,0.0003155018],"genre_scores_gemma":[0.9977621,0.00101836,0.0006955376,0.00002065398,0.0002323568,0.0001915644,0.00001198915,0.00003886297,0.00002850366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1194521,"threshold_uncertainty_score":0.8170245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05164208292037727,"score_gpt":0.2667346750215015,"score_spread":0.2150925921011242,"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."}}