{"id":"W6976584480","doi":"10.6068/dp16e6a537c2846","title":"TREND: International Monetary Fund. Direction of Trade Statistics: Goods, Value of Exports, Free on board (FOB) | Country: United States | Counterpart Country: POLAND, PORTUGAL, QATAR, ROMANIA, RUSSIAN FEDERATION, RWANDA, SAMOA, SAN MARINO, SAO TOME & PRINCIPE, SAUDI ARABIA, SENEGAL, SERBIA & MONTENEGRO, SERBIA, REPUBLIC OF, SEYCHELLES, SIERRA LEONE, SINGAPORE, SLOVAK REPUBLIC, SLOVENIA, SOLOMON ISLANDS, SOMALIA, 1948 - 2018. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 056-002-003","year":2019,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Value (mathematics); Frontier; Payment; Balance of payments; International finance; Goods and services; Exchange rate; Quarter (Canadian coin)","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":[0.001388867,0.002260366,0.002048654,0.005876721,0.0008023695,0.004283025,0.002810856,0.001525959,0.09846225],"category_scores_gemma":[0.01208707,0.00109232,0.001119333,0.01742902,0.0003970868,0.003970725,0.0019681,0.003349745,0.1713147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001879628,"about_ca_system_score_gemma":0.003636899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0438009,"about_ca_topic_score_gemma":0.02756293,"domain_scores_codex":[0.9984108,0.0001627538,0.0003391176,0.000415883,0.000442124,0.0002292995],"domain_scores_gemma":[0.9936916,0.0008018037,0.001179782,0.0006786207,0.003217481,0.0004306062],"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":[0.0000208444,0.000007256801,0.0005191113,0.0002052571,0.00001257801,0.000005759702,0.000008443201,0.00005150824,0.00001437299,0.0002629578,0.9974884,0.001403474],"study_design_scores_gemma":[0.0001753783,0.00001290734,0.006593882,0.0004028701,0.00002530427,0.00001893939,0.0001190358,0.0001502309,0.0001129998,0.0007783672,0.9915815,0.00002855678],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004498817,0.00003295824,0.00002321679,0.00007003327,0.00004962343,0.000007169757,0.9992274,0.00006594959,0.0004786729],"genre_scores_gemma":[0.0002544351,0.00009872168,0.0001312887,0.00004687341,0.00002740051,0.00009610868,0.9981627,0.0000681228,0.001114339],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09846225,"threshold_uncertainty_score":0.329389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02992318755349798,"score_gpt":0.26667005287201,"score_spread":0.236746865318512,"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."}}