{"id":"W4283372046","doi":"10.1016/j.gloenvcha.2022.102484","title":"China’s rising influence on climate governance: Forging a path for the global South","year":2022,"lang":"en","type":"article","venue":"Global Environmental Change","topic":"Sustainability and Climate Change Governance","field":"Environmental Science","cited_by":87,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"China; Technocracy; Corporate governance; Climate governance; Climate change; Political economy of climate change; Political science; Global governance; Global warming; Politics; Economic system; Economics; Natural resource economics; Ecology","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","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004301283,0.000323976,0.0002082414,0.000005590701,0.001400201,0.00005589917,0.0007069469,0.00005922089,0.001530171],"category_scores_gemma":[0.00003239608,0.0002785416,0.0001844287,0.0002791499,0.0003042459,0.000311083,0.001368579,0.0002112397,0.0001611168],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005022235,"about_ca_system_score_gemma":0.000009348594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009821854,"about_ca_topic_score_gemma":0.00009208726,"domain_scores_codex":[0.9972051,0.00008098577,0.0002619598,0.0006919155,0.0008751044,0.0008848988],"domain_scores_gemma":[0.9990443,0.0000414026,0.0002566481,0.0005285379,0.000001729908,0.0001273904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002169721,0.001622639,0.8425937,0.0001738097,0.0001120228,0.0001546906,0.02757063,0.0439794,0.0004902588,0.007503165,0.002975086,0.07065485],"study_design_scores_gemma":[0.00102529,0.0004491307,0.9476647,0.00001879929,0.00004684525,0.00004217645,0.0114569,0.002366166,0.00003639309,0.001314122,0.03509865,0.0004807913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897329,0.0005080319,0.00005428043,0.001385752,0.0003644085,0.001294149,0.00483011,0.00006608522,0.001764252],"genre_scores_gemma":[0.99591,0.0001814804,0.000085114,0.002653624,0.000119088,0.0009249485,0.00004347762,0.00002198116,0.00006024358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.105071,"threshold_uncertainty_score":0.9999667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0146223403728811,"score_gpt":0.2326694955953422,"score_spread":0.2180471552224611,"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."}}