{"id":"W2968064525","doi":"10.5539/eer.v9n2p1","title":"Dynamic Electricity Pricing – Modeling Manufacturer Response and an Application to Cement Processing","year":2019,"lang":"en","type":"article","venue":"Energy and Environment Research","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electricity; Electricity market; Flexibility (engineering); Dynamic pricing; Electricity pricing; Production schedule; Environmental economics; Incentive; Production (economics); Scheduling (production processes); Electricity generation; Electricity retailing; Schedule; Industrial organization; Microeconomics; Computer science; Business; Economics; Operations management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007874495,0.0001350897,0.0001088413,0.0002294115,0.0001416414,0.00006216314,0.0001119229,0.00006007825,0.00002670159],"category_scores_gemma":[0.000005042737,0.0001334537,0.00001039887,0.0001356662,0.00002228447,0.0001481591,0.0001451924,0.0001434257,0.00001745309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000229315,"about_ca_system_score_gemma":0.000006373761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008099228,"about_ca_topic_score_gemma":0.00001993732,"domain_scores_codex":[0.998664,0.00008551194,0.000136923,0.0003753466,0.0003550586,0.0003831284],"domain_scores_gemma":[0.9995406,0.00002969628,0.000009828568,0.0002722788,0.000007941029,0.0001396731],"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":[0.00007859488,0.00002061202,0.0001756201,0.000032502,0.00001123081,0.00000128957,0.000151938,0.9162889,0.02827174,0.0002467428,0.00001599736,0.05470482],"study_design_scores_gemma":[0.0001736342,0.0001115136,0.005270211,0.00001393638,0.00000411675,0.000001336571,0.00009885517,0.9820402,0.003073086,0.0002897504,0.008758517,0.0001647956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8264313,0.0003189019,0.1724249,0.0001501109,0.00002075129,0.0001748968,4.785447e-7,0.00005661686,0.0004220495],"genre_scores_gemma":[0.9976403,0.0005064392,0.001206668,0.00004849652,0.00002860991,0.0001040471,0.000009605694,0.00003158339,0.0004242189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1712182,"threshold_uncertainty_score":0.5442083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01155998171154693,"score_gpt":0.2546693205886584,"score_spread":0.2431093388771114,"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."}}