{"id":"W2393597968","doi":"","title":"An Analysis of Inflation Targeting in Canada and Its Lessons for China","year":2011,"lang":"en","type":"article","venue":"International Business Research","topic":"Environmental and Agricultural Sciences","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inflation targeting; Economics; Monetary policy; China; Inflation (cosmology); Monetary economics; Keynesian economics; Macroeconomics; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007595972,0.0003179723,0.0005382064,0.001677709,0.002283724,0.001988485,0.0007270319,0.0006871943,0.003200005],"category_scores_gemma":[0.003311541,0.0001855632,0.0007408356,0.005358409,0.0007448139,0.0004884325,0.0005667958,0.001271887,0.0001743536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05405104,"about_ca_system_score_gemma":0.07180241,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.995463,"about_ca_topic_score_gemma":0.9950799,"domain_scores_codex":[0.9986511,0.00006612221,0.00002814563,0.00008043447,0.0004979423,0.0006763493],"domain_scores_gemma":[0.9977477,0.0001936526,0.0002083947,0.00005144857,0.001463424,0.0003353851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004883723,0.0001829886,0.4997076,0.0003814359,0.0003859203,0.002243515,0.004282087,0.06323716,0.001860952,0.2480442,0.06905749,0.1101283],"study_design_scores_gemma":[0.00005662034,0.00009952762,0.841753,0.0001687033,0.0004045187,0.0001329654,0.00647483,0.08458098,0.001257916,0.01041522,0.05446495,0.000190866],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8912716,0.005197935,0.001530546,0.01715774,0.00008892525,0.00008840075,0.004359302,0.0001287366,0.08017688],"genre_scores_gemma":[0.9876661,0.002045737,0.0004179049,0.000465939,0.00002726558,0.00001067078,0.001110663,0.0000168541,0.008238816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05405104,"threshold_uncertainty_score":0.3921696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04740084064883778,"score_gpt":0.3157280012858149,"score_spread":0.2683271606369771,"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."}}