{"id":"W4244444641","doi":"10.32920/ryerson.14645877","title":"Demand side management in smart grid","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Smart grid; Demand response; HVAC; Grid; Peak demand; Demand side; Load shifting; Computer science; Load management; Electricity; Consumption (sociology); Reduction (mathematics); Demand management; Consumer demand; Environmental economics; Microeconomics; Economics; Air conditioning; Electrical engineering; Engineering; Mathematics","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":[0.00020146,0.0003528902,0.0003514842,0.000314527,0.00001606101,0.0001225461,0.0003535177,0.000172215,0.0003542026],"category_scores_gemma":[0.000004882264,0.0003966907,0.0001141437,0.0001972084,0.00001291412,0.00006115207,0.001244231,0.0004178877,0.00008798035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002723777,"about_ca_system_score_gemma":0.00001008469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001448357,"about_ca_topic_score_gemma":0.0008451137,"domain_scores_codex":[0.9984552,0.00002996653,0.0003980793,0.0004772427,0.0002565882,0.0003829305],"domain_scores_gemma":[0.9990743,0.00001899132,0.00002499082,0.0007946488,0.00001609934,0.00007098809],"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":[0.000001571409,0.00002745966,0.0006236545,0.0006154809,0.0002907477,0.0003705321,0.00006114864,0.9813016,0.00001303006,0.0008857534,0.01317658,0.002632431],"study_design_scores_gemma":[0.002012109,0.00002414881,0.1478479,0.001452733,0.0003686391,0.0000146745,0.001148173,0.5572062,0.003742094,0.002157059,0.2804995,0.0035269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1228029,0.001564041,0.04221698,0.0002565819,0.009498497,0.0007446799,0.000005777185,0.001254602,0.821656],"genre_scores_gemma":[0.9639248,0.003830818,0.02278886,0.0004021078,0.0006815791,0.0006809892,0.0003257653,0.0002069543,0.007158121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8411219,"threshold_uncertainty_score":0.9998485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010972323830837,"score_gpt":0.2034861270408496,"score_spread":0.1933764038025413,"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."}}