{"id":"W3210585111","doi":"10.1002/eet.1965","title":"Green finance for soft power: An analysis of China's green policy signals and investments in the Belt and Road Initiative","year":2021,"lang":"en","type":"article","venue":"Environmental Policy and Governance","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo; Central University of Finance and Economics","keywords":"Soft power; China; Finance; Action (physics); Power (physics); Government (linguistics); Economics; Business; Political science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0003209346,0.0002241727,0.0005206423,0.0001709777,0.0001088669,0.00003521586,0.000180309,0.00009663437,0.00003341036],"category_scores_gemma":[0.00007318217,0.0002370853,0.00008573544,0.0002703268,0.0003163644,0.0003986616,0.0001592029,0.0001109206,0.000003052755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001587023,"about_ca_system_score_gemma":0.00001950261,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00707252,"about_ca_topic_score_gemma":0.0007609798,"domain_scores_codex":[0.9984913,0.00004994992,0.0005127557,0.0005864345,0.00005740139,0.0003021787],"domain_scores_gemma":[0.9989896,0.00009481215,0.0004923297,0.0003417134,0.00000176731,0.00007975702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007920992,0.0005785927,0.6305495,0.00007198199,0.0006549619,0.00001404582,0.008709843,0.0008210713,0.0006796967,0.3453802,0.00005930362,0.01240165],"study_design_scores_gemma":[0.0008359224,0.0001271616,0.9701758,0.00001071824,0.00003923867,0.000005799284,0.000251172,0.001933044,0.0002201096,0.02367411,0.002488339,0.0002385676],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903369,0.003985148,0.00007992005,0.002104168,0.00001544787,0.0002131755,0.002015688,0.000003651908,0.001245901],"genre_scores_gemma":[0.9922898,0.004583614,0.0002226876,0.002218431,0.00006322633,0.00004721262,0.00006601359,0.00002113549,0.0004878626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3396263,"threshold_uncertainty_score":0.9995395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686232127765352,"score_gpt":0.2257798294979483,"score_spread":0.2089175082202947,"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."}}