{"id":"W6939273535","doi":"10.6068/dp16664b03c5c75","title":"TREND: Federal Reserve Board. Currency Exchange Rates: Exchange Rates | Convert From: China | Convert To: Canada, 01/1981 - 09/2018. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 014-003-001","year":2018,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Foreign-exchange reserves; Currency; Official cash rate; Reserve requirement; China; Reserve currency; Chinese financial system; Open market operation; Exchange rate","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001363049,0.001780462,0.001740967,0.005641033,0.001340489,0.003914048,0.003091252,0.001204178,0.1502203],"category_scores_gemma":[0.01094648,0.001019912,0.0008178985,0.01864835,0.0004427136,0.003113677,0.001592683,0.002779316,0.2353149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005006409,"about_ca_system_score_gemma":0.01110323,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3520278,"about_ca_topic_score_gemma":0.3481215,"domain_scores_codex":[0.9983315,0.0001546104,0.0001929476,0.0004011731,0.0006391389,0.0002807638],"domain_scores_gemma":[0.9895699,0.0007697128,0.0008358406,0.001257589,0.006922456,0.0006444945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000762502,0.000002628721,0.0002276885,0.00004690192,0.00000380434,0.000002139584,0.000003757039,0.00003350539,0.000005505993,0.000188762,0.9986488,0.0008288031],"study_design_scores_gemma":[0.00004580681,0.000003835434,0.003799526,0.0001458052,0.000007469232,0.000007489253,0.00005862547,0.0001156247,0.00008869886,0.0004730281,0.995235,0.00001906718],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002725961,0.00001403076,0.00002254412,0.0000654749,0.00002650946,0.000007539555,0.9988037,0.0001095985,0.0009233279],"genre_scores_gemma":[0.0001788011,0.00004716506,0.0001209719,0.00004035638,0.00001451699,0.00006506374,0.9977391,0.00009431064,0.001699729],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6479722,"threshold_uncertainty_score":0.6999576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04886520964772966,"score_gpt":0.296839489401158,"score_spread":0.2479742797534283,"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."}}