{"id":"W4386078221","doi":"10.1109/tste.2023.3307633","title":"Optimal Design of V2G Incentives and V2G-Capable Electric Vehicles Parking Lots Considering Cost-Benefit Financial Analysis and User Participation","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; York University","keywords":"Revenue; Vehicle-to-grid; Electric vehicle; Grid; Incentive; Profit (economics); Profit maximization; Computer science; Transport engineering; Finance; Engineering; Business; Power (physics); Economics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00157115,0.00142424,0.001534697,0.0007385158,0.0005510671,0.002290352,0.001582762,0.00277409,0.00677316],"category_scores_gemma":[0.003974189,0.001444583,0.0009653134,0.0006221039,0.001217019,0.001658425,0.001664798,0.001573642,0.0004392465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002563242,"about_ca_system_score_gemma":0.003143637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007659928,"about_ca_topic_score_gemma":0.005926455,"domain_scores_codex":[0.9990037,0.0004024875,0.00002537025,0.0001768128,0.0001249855,0.0002666233],"domain_scores_gemma":[0.9984693,0.0008964224,0.0002074236,0.00003831502,0.0001798666,0.0002086338],"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":[0.00005584562,0.00003834894,0.0002785454,0.00004065688,0.00001320764,0.00007749425,0.00001865648,0.9864001,0.0004298016,0.009760407,0.0003757878,0.002511082],"study_design_scores_gemma":[0.00001775639,0.00003851901,0.0001068281,0.000008441474,0.000007867045,0.00001301552,0.00002884806,0.995665,0.0001363316,0.003569786,0.0004007865,0.000006823439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1605657,0.0008150975,0.7939014,0.001674727,0.0001227163,0.0005779124,0.0005411219,0.0002775162,0.04152377],"genre_scores_gemma":[0.9694314,0.0002885098,0.02335368,0.00008304623,0.00001610676,0.0002147592,0.00007651956,0.0000378014,0.006498236],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007659928,"threshold_uncertainty_score":0.02265853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00883708406185952,"score_gpt":0.2125380788919201,"score_spread":0.2037009948300606,"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."}}