{"id":"W2787150389","doi":"10.1109/epec.2017.8286143","title":"An energy management approach for electric vehicle fast charging station","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Electrification; Charging station; State of charge; Photovoltaic system; Electric vehicle; Computer science; Scheduling (production processes); Energy management; Flexibility (engineering); Automotive engineering; Battery (electricity); Real-time computing; Engineering; Electrical engineering; Energy (signal processing); Electricity; Operations management; Power (physics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002769542,0.0005621114,0.0003526149,0.0004499661,0.000738771,0.001214984,0.0008162651,0.0007106352,0.003443989],"category_scores_gemma":[0.0002802818,0.0002294507,0.000466713,0.0004476309,0.0002706879,0.0005842714,0.000556241,0.0004518257,0.0002895192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001327417,"about_ca_system_score_gemma":0.001313362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01994269,"about_ca_topic_score_gemma":0.02136469,"domain_scores_codex":[0.9998404,0.00003272756,0.000006810996,0.000030574,0.00005587155,0.00003358563],"domain_scores_gemma":[0.9999266,0.00001868671,0.00001054132,0.000003658517,0.00003298731,0.000007545029],"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":[0.00004102145,0.00006603095,0.0006396428,0.00008815875,0.00002456729,0.0002896826,0.0001351955,0.8872126,0.006729323,0.03765366,0.001806259,0.06531399],"study_design_scores_gemma":[0.000005132911,0.00004078862,0.0002321579,0.000005749043,0.000007992366,0.00003001341,0.00007340635,0.9930119,0.0004727257,0.003855584,0.00225736,0.000007150795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0446219,0.0007563133,0.9166973,0.0006853792,0.00009280824,0.0001944212,0.0000992584,0.0002329817,0.03661966],"genre_scores_gemma":[0.9442385,0.0004857357,0.04148312,0.00007388123,0.00004537804,0.0001163275,0.0000596085,0.00002264927,0.01347495],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01994269,"threshold_uncertainty_score":0.03965324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01956204853498857,"score_gpt":0.2787073898028657,"score_spread":0.2591453412678771,"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."}}