{"id":"W2302675721","doi":"10.1109/smartgridcomm.2015.7436325","title":"Distributed demand curtailment via water-filling","year":2015,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Scalability; Computer science; Smart grid; Flexibility (engineering); Demand response; Carbon footprint; Distributed computing; Grid; Peak demand; Aggregate (composite); Reduction (mathematics); Electricity; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004583935,0.0005410678,0.0007794265,0.0002666525,0.0004585839,0.0006869272,0.001259494,0.0006339375,0.002360885],"category_scores_gemma":[0.001205865,0.0002793926,0.000353755,0.0004610144,0.0007135341,0.001094529,0.001415007,0.000596463,0.0004116991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005118616,"about_ca_system_score_gemma":0.0006433715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002374526,"about_ca_topic_score_gemma":0.002985421,"domain_scores_codex":[0.9996448,0.00009232654,0.0000163551,0.0001016147,0.00008038224,0.00006448014],"domain_scores_gemma":[0.9995585,0.000193496,0.00007647809,0.00007036675,0.00006315617,0.00003791833],"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":[0.0003465883,0.0002492825,0.0008561645,0.0001873848,0.00005827087,0.0003553132,0.0002821973,0.750469,0.0479534,0.03321768,0.005607463,0.1604172],"study_design_scores_gemma":[0.00002388311,0.0000534776,0.00007887853,0.000005212828,0.000007055244,0.00003892664,0.00003214179,0.9869282,0.003269475,0.007644615,0.00190717,0.00001098191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05763949,0.0001712489,0.934705,0.000376542,0.000063632,0.00009388447,0.00008662249,0.0009532225,0.005910384],"genre_scores_gemma":[0.9608074,0.00008407671,0.03606502,0.000099889,0.00002007044,0.00005492294,0.00003779373,0.00004303919,0.002787781],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002374526,"threshold_uncertainty_score":0.007897913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01368054463235681,"score_gpt":0.1913397500517718,"score_spread":0.177659205419415,"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."}}