{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006304376,0.00007787115,0.00006860257,0.0001144534,0.0001755534,0.00009039005,0.000380929,0.00003869496,0.00001020031],"category_scores_gemma":[0.000008689243,0.00007604561,0.00001677951,0.000058912,0.00001513829,0.0003048145,0.00004730003,0.00005926295,0.000004112513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006803039,"about_ca_system_score_gemma":0.000001865602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008452611,"about_ca_topic_score_gemma":0.000004104916,"domain_scores_codex":[0.9993866,0.000003650316,0.00007646004,0.0001546665,0.00009862315,0.0002799925],"domain_scores_gemma":[0.999456,0.000009774728,0.00001697631,0.0004686203,0.00002006304,0.00002853497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000103365,0.00003495895,0.0002242302,0.00009925479,0.0000374128,0.000002545713,0.00002099779,0.03871549,0.05441739,0.01902807,0.0006720191,0.8867373],"study_design_scores_gemma":[0.0002351816,0.00003694866,0.001255299,0.000002278028,0.000002643671,4.548744e-7,0.00008570661,0.9426754,0.05296273,0.0009816623,0.001648106,0.0001135816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0215236,0.00002402688,0.9612446,0.0000417912,0.00003123976,0.0001798455,0.000002875609,0.00059064,0.01636132],"genre_scores_gemma":[0.9603708,0.00006811926,0.03859878,0.00001401254,0.00002600503,0.0001863662,0.00001998381,0.00002626695,0.0006897076],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9388472,"threshold_uncertainty_score":0.310105,"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."}}