{"id":"W2526713913","doi":"10.1109/tste.2016.2614397","title":"Electric Vehicle Charging Facility as a Smart Energy Microhub","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Majmaah University","keywords":"Electric vehicle; Renewable energy; Distributed generation; Smart grid; Energy storage; Computer science; Reliability engineering; Automotive engineering; Photovoltaic system; Electric power system; Engineering; Grid; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001029451,0.0003295433,0.0002672494,0.000366522,0.0002815554,0.00005708326,0.0002336642,0.0002130157,0.0005485801],"category_scores_gemma":[0.000006131675,0.0002697224,0.0001643687,0.0008273642,0.00003653089,0.0003355389,0.000002066736,0.0002192964,0.00005202515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000559758,"about_ca_system_score_gemma":0.0001037557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008028468,"about_ca_topic_score_gemma":0.00005529663,"domain_scores_codex":[0.998089,0.00004711485,0.0002992423,0.0003804844,0.0002389765,0.0009451753],"domain_scores_gemma":[0.999143,0.00009504169,0.00003545206,0.0004069624,0.0001253675,0.0001941534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001505596,0.0001452757,0.00002390459,0.00009843799,0.0002476872,0.0001307516,0.0001354236,0.04305897,0.3824609,0.008735037,0.00446462,0.5603484],"study_design_scores_gemma":[0.0008390408,0.000212377,0.0000497043,0.00002319729,0.00003322984,0.00004806261,0.000125537,0.007682022,0.8046086,0.002764757,0.1830762,0.0005372237],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1290961,0.0005896374,0.8625906,0.0002936611,0.0003869405,0.0001041274,0.00002574599,0.0008052981,0.006107958],"genre_scores_gemma":[0.9811853,0.0005630344,0.00004310657,0.0002458868,0.00007494906,0.00008373335,0.000002731107,0.00005564451,0.01774559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8625475,"threshold_uncertainty_score":0.9999755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003370468177104277,"score_gpt":0.1757023198990084,"score_spread":0.1723318517219041,"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."}}