{"id":"W2144278408","doi":"10.1109/infcom.2012.6195538","title":"Towards optimal energy store-carry-and-deliver for PHEVs via V2G system","year":2012,"lang":"en","type":"article","venue":"","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Energy storage; Vehicle-to-grid; Electricity pricing; Grid; Electricity; Energy flow; Smart grid; Mathematical optimization; Electric vehicle; Battery (electricity); Automotive engineering; Energy (signal processing); Simulation; Real-time computing; Power (physics); Engineering; Electrical engineering; Electricity market; Mathematics","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":[0.00006586118,0.0001370343,0.0001504347,0.00003883014,0.00004480528,0.00001920467,0.00007521644,0.0001068584,0.00008045452],"category_scores_gemma":[0.000002213221,0.0001121242,0.00005213689,0.00006724692,0.000009917897,0.0001969677,0.00001967785,0.00006776461,0.000006851678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007159364,"about_ca_system_score_gemma":0.000005434007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006057643,"about_ca_topic_score_gemma":0.000002951135,"domain_scores_codex":[0.9993352,0.00000605761,0.0001320732,0.00009573762,0.00008634399,0.0003446458],"domain_scores_gemma":[0.9997101,0.00001591258,0.00001429437,0.0001109521,0.00002859033,0.0001201895],"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":[0.00008165849,0.00004855734,0.001571661,0.001079829,0.0006273037,0.000004819161,0.001439528,0.03301206,0.02999045,0.2225424,0.08537206,0.6242297],"study_design_scores_gemma":[0.0009045958,0.000148181,0.002509155,0.0000265988,0.00008506557,0.00009967274,0.0002315642,0.7925639,0.02806767,0.0001353162,0.1745958,0.0006324778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2239093,0.004585265,0.7396157,0.00004387894,0.0009523716,0.0002297708,0.00001979569,0.0007958811,0.02984795],"genre_scores_gemma":[0.9896426,0.00003190608,0.00935539,0.00005832404,0.0004865375,0.00002234423,0.000006783416,0.00003369148,0.0003624857],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7657332,"threshold_uncertainty_score":0.4572293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005059364618180473,"score_gpt":0.1813415722359251,"score_spread":0.1762822076177446,"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."}}