{"id":"W6957909487","doi":"10.6068/dp15884aaf66829","title":"TREND: Federal Reserve Board. Currency Exchange Rates: Exchange Rates | Convert From: United States | Convert To: Canada, 01/04/1971 - 11/10/2016. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 014-003-001","year":2016,"lang":"en","type":"other","venue":"Data Planet","topic":"Biodiesel Production and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Currency; Foreign-exchange reserves; Reserve requirement; Federal Reserve Economic Data; Open market operation; Reserve currency; Monetary reform; Exchange rate; Official cash 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":[0.001486954,0.001984515,0.001853185,0.006072107,0.001426449,0.0046827,0.003156703,0.001376154,0.1472993],"category_scores_gemma":[0.0114999,0.001037188,0.0009176719,0.01751734,0.0004434428,0.003703579,0.001610354,0.003178982,0.259596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004669072,"about_ca_system_score_gemma":0.008911607,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2658317,"about_ca_topic_score_gemma":0.2530644,"domain_scores_codex":[0.9978766,0.0001907597,0.0002486024,0.000528599,0.0008569084,0.0002984668],"domain_scores_gemma":[0.987793,0.0009089631,0.001057945,0.001373997,0.008248526,0.0006175785],"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":[0.000008610878,0.000003268214,0.0002349561,0.00004540118,0.000003784241,0.000002186903,0.000003652817,0.00003466641,0.000006020627,0.0002325355,0.9984352,0.0009896018],"study_design_scores_gemma":[0.00003859601,0.00000384782,0.002875655,0.0001286561,0.000006298151,0.000006628647,0.00005174962,0.00009092092,0.00007148391,0.0004426735,0.9962682,0.00001526922],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003420914,0.00002264573,0.00003162036,0.00009146531,0.00004578706,0.00001028556,0.9980491,0.0001322506,0.001582532],"genre_scores_gemma":[0.0002033753,0.00006199644,0.0001386416,0.00005210656,0.00002276649,0.00007191775,0.9971898,0.0001087382,0.002150653],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7341683,"threshold_uncertainty_score":0.5285687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03470485495051821,"score_gpt":0.2800020573545269,"score_spread":0.2452972024040087,"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."}}