{"id":"W2354988967","doi":"","title":"An Analysis of the Intermediate Target Choice of China's Monetary Policy","year":2007,"lang":"en","type":"article","venue":"Huadong Li-Gong Daxue xuebao","topic":"Evaluation Methods in Various Fields","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Monetary policy; Money supply; Inflation (cosmology); Variance decomposition of forecast errors; Monetary economics; Exchange rate; Variance (accounting); Interest rate; Quarter (Canadian coin); Granger causality; Causality (physics); Inflation targeting; Econometrics; Macroeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002380681,0.0001909481,0.0003882454,0.0003034672,0.0001186904,0.00001771132,0.000944504,0.0001594781,0.001590326],"category_scores_gemma":[0.0006544293,0.0001494501,0.0002580105,0.00214223,0.0004267172,0.0002668901,0.0003015695,0.0002884238,0.0000257418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001448687,"about_ca_system_score_gemma":0.00003956749,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007104605,"about_ca_topic_score_gemma":0.002527078,"domain_scores_codex":[0.9975403,0.0003678713,0.0006428428,0.0003781338,0.0007069402,0.0003639325],"domain_scores_gemma":[0.9980043,0.0003121945,0.0004292494,0.001091281,0.00003021739,0.0001327616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002601608,0.000170602,0.9180117,0.00001566726,0.0001818376,0.000002027876,0.001993207,0.05244732,0.01957664,0.0003246958,0.0002125034,0.00703777],"study_design_scores_gemma":[0.0001925968,0.00006716772,0.9621484,0.0000126569,0.0002712315,0.000001016642,0.0001017718,0.02004357,0.01586122,0.0007544274,0.0003948747,0.0001510271],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750364,0.00003704102,0.01466559,0.0002166388,0.0002357408,0.0002208709,0.00002861771,0.00003227507,0.009526861],"genre_scores_gemma":[0.9782501,0.000009262874,0.02076646,0.000290479,0.0001112856,0.000005042479,0.00002030423,0.00001932679,0.000527686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04413672,"threshold_uncertainty_score":0.9995072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01910849243750047,"score_gpt":0.3408196971467733,"score_spread":0.3217112047092728,"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."}}