{"id":"W2998110655","doi":"10.3390/electronics9010080","title":"EV Charging Behavior Analysis Using Hybrid Intelligence for 5G Smart Grid","year":2020,"lang":"en","type":"article","venue":"Electronics","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Smart grid; Scheduling (production processes); Quality of service; Cloud computing; Architecture; Distributed computing; Electric vehicle; Grid; Internet of Things; Real-time computing; Embedded system; Computer network; Engineering; Power (physics); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003869031,0.0004797621,0.0003838194,0.001378821,0.0002654833,0.0006201956,0.000291227,0.0003015102,0.0005405459],"category_scores_gemma":[0.0007617503,0.000114673,0.0004851928,0.0009921659,0.0001890372,0.0005633104,0.000278271,0.0002687536,0.0001820374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004329325,"about_ca_system_score_gemma":0.0002364677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00497037,"about_ca_topic_score_gemma":0.003318631,"domain_scores_codex":[0.9997358,0.00006528921,0.00001946511,0.00004544631,0.00008623422,0.0000477493],"domain_scores_gemma":[0.9998129,0.00006116257,0.00002917039,0.00002194417,0.00006268929,0.00001213746],"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":[0.0006336832,0.0003699976,0.07209253,0.0001360237,0.0002515726,0.0004580662,0.0002436886,0.5784719,0.01769015,0.003711917,0.00219644,0.323744],"study_design_scores_gemma":[0.00000331052,0.00003626557,0.00646797,0.000003339388,0.0000112433,0.0000367553,0.00004590379,0.9909273,0.001573922,0.0006479743,0.0002383648,0.00000747833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6000828,0.000335463,0.3920404,0.0002283324,0.00006617802,0.0001311948,0.0002863312,0.001260481,0.005568742],"genre_scores_gemma":[0.9825568,0.00005920307,0.01672795,0.00002805509,0.000007055939,0.000023329,0.0001688896,0.00001056651,0.0004182782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00497037,"threshold_uncertainty_score":0.009882867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01460065267766252,"score_gpt":0.2363329945941365,"score_spread":0.221732341916474,"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."}}