{"id":"W6976757545","doi":"10.6068/dp164f800d16340","title":"TREND: Federal Reserve Board. Currency Exchange Rates: Exchange Rates | Convert From: United States | Convert To: Australia, Canada, China, Mexico, United Kingdom, 01/2017 - 07/2018. 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; Reserve currency; Official cash rate; Federal Reserve Economic Data; Open market operation; Reserve requirement; Special drawing rights; 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":[0.001529981,0.002013728,0.001662474,0.004873995,0.0009387222,0.00371244,0.002800994,0.00145227,0.1549491],"category_scores_gemma":[0.0123221,0.0009268263,0.0009503288,0.01295177,0.0003673898,0.003953991,0.0016681,0.003098271,0.2885244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001780945,"about_ca_system_score_gemma":0.003189366,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03995246,"about_ca_topic_score_gemma":0.03816027,"domain_scores_codex":[0.9984022,0.0002203497,0.0002548784,0.0004513543,0.0004657249,0.00020562],"domain_scores_gemma":[0.9926818,0.001010055,0.0009690783,0.001153557,0.003718263,0.0004672537],"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":[0.00001112696,0.000004117521,0.0002682431,0.00006583838,0.000004997762,0.000002869155,0.000004553236,0.00003724703,0.000008653174,0.0002254675,0.9983218,0.001045142],"study_design_scores_gemma":[0.0000688304,0.00000681824,0.002875753,0.0001705302,0.000008875108,0.00001153621,0.00006539773,0.0001276397,0.00008866956,0.0007477764,0.9958091,0.00001901383],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004095169,0.00002189682,0.00004476896,0.00009995029,0.00005329146,0.00001006326,0.9984398,0.0001616152,0.001127698],"genre_scores_gemma":[0.0002458854,0.00005846002,0.000178486,0.0000676281,0.00002803373,0.0001025123,0.9975761,0.000127391,0.001615433],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9600475,"threshold_uncertainty_score":0.5183563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.098527017991034,"score_gpt":0.3313108352006487,"score_spread":0.2327838172096147,"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."}}