{"id":"W4283829550","doi":"10.1016/j.energy.2022.124739","title":"Combined effects of carbon pricing and power market reform on CO2 emissions reduction in China's electricity sector","year":2022,"lang":"en","type":"article","venue":"Energy","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"National Natural Science Foundation of China","keywords":"Electricity; China; Greenhouse gas; Electricity market; Natural resource economics; Reduction (mathematics); Environmental economics; Economics; Environmental science; Electricity pricing; Business; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001782093,0.0004781717,0.0009290657,0.0007784624,0.0007998233,0.002839481,0.0009038368,0.001770335,0.004886691],"category_scores_gemma":[0.004006956,0.0002921082,0.001374837,0.001007116,0.001474167,0.001715082,0.001338684,0.001320377,0.0002268114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006780141,"about_ca_system_score_gemma":0.00880817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1234859,"about_ca_topic_score_gemma":0.162098,"domain_scores_codex":[0.9983557,0.0003118806,0.00007866829,0.000136258,0.0002762416,0.0008413064],"domain_scores_gemma":[0.9974456,0.0006711617,0.0006642255,0.0001341086,0.0006016705,0.000483244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006632802,0.002995831,0.4261043,0.001042924,0.002229604,0.005313308,0.001466004,0.3070062,0.02269912,0.09688905,0.0193096,0.1083113],"study_design_scores_gemma":[0.0008106497,0.001401447,0.8106641,0.00008304123,0.002344214,0.0002007327,0.003552929,0.138614,0.01133923,0.01704936,0.01373164,0.0002086832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905342,0.0006186839,0.0002380143,0.002245119,0.00009099035,0.00003228623,0.0002337571,0.00004271702,0.005964241],"genre_scores_gemma":[0.9986896,0.0001427538,0.00004379868,0.0001737975,0.00003189946,0.000004852307,0.00005855459,0.000002986088,0.0008516835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1234859,"threshold_uncertainty_score":0.2455342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01508681447492991,"score_gpt":0.201083852115729,"score_spread":0.1859970376407991,"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."}}