{"id":"W6939242537","doi":"10.6068/dp16e6a46a69439","title":"TREND: International Monetary Fund. Direction of Trade Statistics: Goods, Value of Exports, Free on board (FOB) | Country: United States | Counterpart Country: AZERBAIJAN, REP. OF, BENIN, BERMUDA, BHUTAN, BOLIVIA, BOSNIA & HERZEGOVINA, BOTSWANA, BRAZIL, BRUNEI DARUSSALAM, BULGARIA, BURKINA FASO, BURUNDI, CAMBODIA, CAMEROON, CANADA, CAPE VERDE, CENTRAL AFRICAN REP., CHAD, CHILE, CHINA,P.R.: MAINLAND, 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":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Value (mathematics); Frontier; International finance; Special drawing rights; Exchange rate; Monetary system; Payment; Monetary policy","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":[0.001387297,0.002004026,0.001772339,0.005556058,0.000953282,0.003748233,0.003042578,0.001800436,0.1174743],"category_scores_gemma":[0.01286407,0.001111707,0.001047765,0.0172207,0.0004188204,0.003965923,0.001993749,0.003524877,0.1805702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002228139,"about_ca_system_score_gemma":0.004288935,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06264826,"about_ca_topic_score_gemma":0.04462349,"domain_scores_codex":[0.9985412,0.0001686515,0.0002679474,0.0003903411,0.000387729,0.0002441961],"domain_scores_gemma":[0.9934112,0.0008857647,0.001065903,0.0007963794,0.003369291,0.0004714029],"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":[0.00001288031,0.000005361023,0.0003417074,0.0001365934,0.000007686645,0.000004425825,0.000007091833,0.0000366188,0.00001040171,0.000236144,0.9982495,0.000951639],"study_design_scores_gemma":[0.0001323415,0.000007995605,0.004903296,0.0003144816,0.00001673116,0.00001519179,0.0001068469,0.0001112611,0.00008996859,0.0007394988,0.9935395,0.00002291329],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003407494,0.00002301882,0.00002243082,0.00006975706,0.00004168332,0.000006187028,0.9992867,0.00005624725,0.0004599792],"genre_scores_gemma":[0.0002359694,0.00006946742,0.000143955,0.00004580604,0.00002231269,0.00009863006,0.9980612,0.000065419,0.001257118],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9373518,"threshold_uncertainty_score":0.3929905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01109107842551925,"score_gpt":0.2190808012049904,"score_spread":0.2079897227794711,"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."}}