{"id":"W2030343799","doi":"10.1109/tsg.2011.2177103","title":"A Water-Filling Based Scheduling Algorithm for the Smart Grid","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Scheduling (production processes); Smart grid; Grid; Distributed computing; Computation; Demand response; Power consumption; Fair-share scheduling; Real-time computing; Electricity; Mathematical optimization; Computer network; Power (physics); Algorithm; Engineering; Quality of service","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":[0.0005573164,0.0003755234,0.0002646002,0.0002279329,0.000505457,0.00008450027,0.0003040227,0.0001274891,0.0001996564],"category_scores_gemma":[0.000004087069,0.000279029,0.0002970582,0.0002547903,0.00005360697,0.0003105198,0.000002874471,0.0003735241,0.0002470351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001712094,"about_ca_system_score_gemma":0.00001540207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000513438,"about_ca_topic_score_gemma":0.00003422733,"domain_scores_codex":[0.998075,0.00004026245,0.0003847305,0.0002906597,0.000322242,0.000887092],"domain_scores_gemma":[0.998841,0.0002990622,0.0000297184,0.0005855795,0.00005817488,0.0001864384],"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":[0.00001805934,0.0001070659,0.00002230109,0.00005363587,0.000224831,0.00000149179,0.0001544608,0.971227,0.001301782,0.00001451062,0.001652954,0.02522194],"study_design_scores_gemma":[0.0006972034,0.00005203136,0.00008756781,0.00003844084,0.0001794744,0.000005846271,0.00008565082,0.7283362,0.1260916,0.000006581986,0.1440275,0.0003919114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006361203,0.0001815533,0.9732056,0.0003588612,0.01815072,0.0005662694,0.0000900134,0.000703097,0.0003826993],"genre_scores_gemma":[0.9559812,0.000133323,0.03804239,0.0005638408,0.003322384,0.001250661,0.00005351102,0.0002290961,0.0004235887],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.94962,"threshold_uncertainty_score":0.9999662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01878006319326371,"score_gpt":0.2206430539342364,"score_spread":0.2018629907409727,"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."}}