{"id":"W2007907648","doi":"10.1016/j.techfore.2006.09.004","title":"Scenario development in China's electricity sector","year":2006,"lang":"en","type":"article","venue":"Technological Forecasting and Social Change","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Greenhouse gas; Electricity; Tonne; Coal; Natural resource economics; Consumption (sociology); Sustainability; Electricity generation; Environmental science; China; Economics; Natural gas; Agricultural economics; Investment (military); Environmental economics; Engineering; Waste management; Geography","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":[0.0003073311,0.0001318272,0.0001518059,0.00003940062,0.0002642862,0.00001837718,0.0001049442,0.0001849012,0.0001840668],"category_scores_gemma":[0.00004032075,0.0001095477,0.00002663477,0.0002615918,0.0003150257,0.00009097374,0.000210202,0.0002321146,0.00001444341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004103013,"about_ca_system_score_gemma":0.000003345053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001325306,"about_ca_topic_score_gemma":0.0007449504,"domain_scores_codex":[0.9989966,0.00003045694,0.0001664079,0.000256279,0.0001548675,0.0003953934],"domain_scores_gemma":[0.9998468,0.0000179257,0.00004251165,0.00006029541,0.000001547979,0.0000308969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001600471,0.0002236586,0.8458301,0.0000142939,0.000001844965,0.00002715364,0.001406862,0.000005262225,0.0006095057,0.0007806011,0.00005636078,0.1510283],"study_design_scores_gemma":[0.0001999048,0.00005287281,0.991702,0.000004468286,0.00000204956,0.000005335652,0.0001256174,0.0003766626,0.0006317208,0.004420891,0.002300123,0.0001783297],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996251,0.00004011202,0.00005518409,0.000337343,0.00001112912,0.0002250449,0.000001271361,0.0001255641,0.002953379],"genre_scores_gemma":[0.9991006,0.000003236279,0.0005900643,0.00006501204,0.00003589932,0.00004502896,0.000005205797,0.00000687075,0.0001480885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.15085,"threshold_uncertainty_score":0.4467225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03763272651950719,"score_gpt":0.228157879663294,"score_spread":0.1905251531437868,"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."}}