{"id":"W3012039178","doi":"10.23977/isspj.2020.51003","title":"Analysis of Electric Vehicle Charging Behavior under Differential Privacy Protection","year":2020,"lang":"en","type":"article","venue":"Information Systems and Signal Processing Journal","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cluster analysis; Electric vehicle; Computer science; Outlier; Reliability (semiconductor); Automotive engineering; Cluster (spacecraft); Power grid; Grid; Differential privacy; Service (business); Charging station; Process (computing); Privacy protection; Power (physics); Computer security; Reliability engineering; Data mining; Engineering; Computer network; Artificial intelligence; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001035134,0.0002707155,0.0003718288,0.0006929932,0.0004041951,0.0007024161,0.0005395004,0.0004602388,0.0005666502],"category_scores_gemma":[0.005871973,0.0001423199,0.0003144628,0.001083888,0.0004993568,0.0009861863,0.0004854662,0.0004195151,0.0001738098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006861034,"about_ca_system_score_gemma":0.0005358012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002896789,"about_ca_topic_score_gemma":0.001329216,"domain_scores_codex":[0.9988404,0.0002325726,0.00006303657,0.0002314283,0.0004383808,0.0001941859],"domain_scores_gemma":[0.9979886,0.0007747206,0.0002671943,0.0003651734,0.0005418066,0.00006255254],"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":[0.001512965,0.0003513743,0.1527593,0.0002282207,0.0002309103,0.001644345,0.001056765,0.5363486,0.05503814,0.02021374,0.002230181,0.2283854],"study_design_scores_gemma":[0.000008741418,0.00009946479,0.01795616,0.000004995995,0.00001906399,0.000351148,0.0002705807,0.9613395,0.01564253,0.003655109,0.0006315657,0.00002128922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8293852,0.0001022156,0.1675221,0.0001995356,0.00002087384,0.00004545947,0.0001795393,0.0003812707,0.002163851],"genre_scores_gemma":[0.995562,0.00003060961,0.003926602,0.00001025879,0.000003322656,0.000007934134,0.0001084236,0.000007670332,0.0003432543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002896789,"threshold_uncertainty_score":0.005759835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01227127198599343,"score_gpt":0.2091062990496692,"score_spread":0.1968350270636758,"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."}}