{"id":"W2793266273","doi":"10.1016/j.energy.2018.01.169","title":"Forecasting China's electricity consumption using a new grey prediction model","year":2018,"lang":"en","type":"article","venue":"Energy","topic":"Grey System Theory Applications","field":"Decision Sciences","cited_by":264,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Nanjing University of Aeronautics and Astronautics; Government of Jiangsu Province; National Natural Science Foundation of China","keywords":"Electricity; China; Consumption (sociology); Econometrics; Operations research; Economics; Engineering; Computer science; Geography; 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":[0.001238243,0.0001188594,0.0001654081,0.0002415522,0.0003804016,0.0001508288,0.0003822772,0.00008765442,0.0001939304],"category_scores_gemma":[0.0007903966,0.0001010141,0.00006649796,0.0007364835,0.00008057691,0.0003602937,0.00007844868,0.00006877617,0.0001271349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009508261,"about_ca_system_score_gemma":0.0001263348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003429912,"about_ca_topic_score_gemma":0.0001871745,"domain_scores_codex":[0.9980766,0.0001557887,0.000482023,0.0004340364,0.0006067653,0.0002448238],"domain_scores_gemma":[0.9985963,0.0002056022,0.0002791507,0.0005272815,0.0002587889,0.0001328808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002381701,0.0002084209,0.02605547,0.00001185121,0.00008969293,0.000005243145,0.003317658,0.2037178,0.08687594,0.3670283,0.03303118,0.2794203],"study_design_scores_gemma":[0.0001442983,0.00003057701,0.001082029,0.00001057278,0.000009525103,0.00003102495,0.00001682155,0.8790577,0.003558534,0.1139025,0.002069307,0.00008706101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4174724,0.00002684507,0.5789158,0.00005474445,0.000165144,0.0000613876,0.000006408657,0.00006392719,0.003233289],"genre_scores_gemma":[0.9900728,0.000001770228,0.006419383,0.00008101665,0.0004787582,0.00001106946,0.000004276329,0.00001414531,0.002916739],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6753399,"threshold_uncertainty_score":0.4119235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1824952355676884,"score_gpt":0.3621006321507219,"score_spread":0.1796053965830335,"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."}}