{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003309834,0.00003912616,0.00006403558,0.00008211157,0.000054201,0.00001068791,0.0002111397,0.00001390463,0.000774447],"category_scores_gemma":[0.00006279915,0.00002793913,0.00001122892,0.0006377517,0.00006137717,0.0003012893,0.00009411587,0.00004298096,0.000002175673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002178851,"about_ca_system_score_gemma":0.00002028505,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.838234,"about_ca_topic_score_gemma":0.8093008,"domain_scores_codex":[0.9991493,0.00002785401,0.0001214614,0.0001614698,0.00041408,0.0001258237],"domain_scores_gemma":[0.9998166,0.00004342635,0.00003518396,0.00003832218,0.00002755634,0.000038904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001545214,0.00004031929,0.9552034,0.0000027326,0.00001314199,0.000001383687,0.0003074244,0.007742234,0.03427181,0.0001309906,0.00003748038,0.002233673],"study_design_scores_gemma":[0.00005737011,0.000009154838,0.9787557,0.000003749798,0.000004007033,2.212249e-7,0.0001831129,0.01828668,0.002446328,0.0001469486,0.00006751509,0.00003923576],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985223,0.00001174139,0.00003885542,0.000405986,0.00002930393,0.00008510808,0.00001870357,0.000001483184,0.0008864707],"genre_scores_gemma":[0.9996494,0.00002562585,0.0001952028,0.000008077648,0.000009776089,0.00001379623,0.00002655633,0.00000143666,0.00007012123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03182549,"threshold_uncertainty_score":0.8479651,"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."}}