{"id":"W2754216624","doi":"10.1109/tii.2017.2750638","title":"Evaluating Electric Vehicles’ Response Time to Regulation Signals in Smart Grids","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Informatics","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"News aggregator; Computer science; Smart grid; Network packet; Computer network; Wireless; Real-time computing; Demand response; Flexibility (engineering); Engineering; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007148233,0.0006493553,0.0004142912,0.0005219698,0.0001968604,0.000462662,0.0004844823,0.0006908831,0.0008329953],"category_scores_gemma":[0.003556292,0.0002090176,0.0002915479,0.0004709959,0.000257427,0.0007306983,0.0003679426,0.0004209009,0.000172965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008383983,"about_ca_system_score_gemma":0.0004027573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008185858,"about_ca_topic_score_gemma":0.003027131,"domain_scores_codex":[0.9995149,0.0001363114,0.00003047624,0.00008137661,0.0001415088,0.00009532599],"domain_scores_gemma":[0.997615,0.001689377,0.000232495,0.0001017871,0.0002604987,0.0001009349],"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":[0.0002249823,0.00008308949,0.007242041,0.00004895623,0.00002653108,0.00008013885,0.00002794032,0.9817808,0.00445668,0.0003996368,0.0001705527,0.005458697],"study_design_scores_gemma":[0.000005139913,0.00009966175,0.001956825,0.000002546284,0.000007387576,0.00001519106,0.00002294236,0.9956068,0.00208053,0.0001270865,0.00007005081,0.000005900774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9614011,0.0002340853,0.03620597,0.00007121145,0.00003245008,0.00002819156,0.0001832079,0.0003340042,0.001509839],"genre_scores_gemma":[0.9985903,0.00003914885,0.001122963,0.000004958126,0.00000212587,0.000008115479,0.00007552554,0.000008201525,0.0001485485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008185858,"threshold_uncertainty_score":0.01627642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04022107657627398,"score_gpt":0.282044746685532,"score_spread":0.241823670109258,"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."}}