{"id":"W3011707620","doi":"10.1109/tsg.2020.2979435","title":"Demand Response Cooperative and Demand Charge","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Demand response; Schedule; Mathematical optimization; Operations research; Electricity market; Electricity; Probabilistic logic; Scheduling (production processes); Computer science; Linear programming; Piecewise linear function; Stochastic optimization; Engineering; Mathematics; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001614429,0.0002267896,0.0002097513,0.0001044492,0.0001561648,0.00005090202,0.0001002789,0.0000728242,0.0002337263],"category_scores_gemma":[0.000007568467,0.000230142,0.0000577894,0.0002576956,0.0000497159,0.0001668288,0.000001945962,0.0002327447,0.0002489841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004702877,"about_ca_system_score_gemma":0.00001231899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000553629,"about_ca_topic_score_gemma":0.00001278805,"domain_scores_codex":[0.9990182,0.00007842502,0.0002075511,0.0002805984,0.0001625441,0.0002527091],"domain_scores_gemma":[0.9994541,0.0001092314,0.0000152488,0.0001909085,0.00002631052,0.0002041668],"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":[0.0005847561,0.00006090947,0.00006982122,0.00008137985,0.0002722383,0.00004517219,0.001236343,0.9644968,0.01740856,0.00005827367,0.01434395,0.001341811],"study_design_scores_gemma":[0.0033672,0.0007627436,0.003802849,0.00009331237,0.0002337284,0.00003686748,0.0002698951,0.4862283,0.3011101,0.00001415154,0.202802,0.001278809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3350428,0.0001954276,0.6589941,0.001617117,0.001724826,0.000310172,0.00007071584,0.0006643812,0.001380479],"genre_scores_gemma":[0.9981278,0.0002457509,0.0002674631,0.0006888349,0.0001943582,0.00007309316,0.000003344073,0.00005080748,0.0003485351],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.663085,"threshold_uncertainty_score":0.9384919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01445524530868801,"score_gpt":0.2055982588610046,"score_spread":0.1911430135523166,"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."}}