{"id":"W6938947891","doi":"10.6068/dp1617889589122","title":"TREND: United States Census Bureau. US Trade by Commodity Group: Exports | Country: Brazil, China, India, Russia, South Africa | WCO Harmonized Trade Num: 41, 42, 43, 44, 45, 46, 47, 48, 49, 50 | Consumer Item: Raw Hides And Skins (no Furskins) And Leather, Leather Art; Saddlery Etc; Handbags Etc; Gut Art, Furskins And Artificial Fur; Manufactures Thereof, Wood And Articles Of Wood; Wood Charcoal, Cork And Articles Of Cork, Mfr Of Straw, Esparto Etc.; Basketware & Wickerwrk, Wood Pulp Etc; Recovd (waste & Scrap) ppr & pprbd, Paper & Paperboard & Articles (inc Papr Pulp Artl), Printed Books, Newspapers Etc; Manuscripts Etc, Silk, Including Yarns And Woven Fabric Thereof, 01/2002 - 10/2017. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 001-035-001","year":2018,"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":"Census; Liberian dollar; Commodity; Paperboard; CONQUEST; Value (mathematics); Landlocked country","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":[0.000919728,0.001715634,0.001487537,0.003929242,0.0007282978,0.002040313,0.002250527,0.001145299,0.07645077],"category_scores_gemma":[0.009278694,0.0007407731,0.001344561,0.0133759,0.0003208879,0.002432063,0.001362921,0.002306139,0.08132539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001493474,"about_ca_system_score_gemma":0.003482721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07577019,"about_ca_topic_score_gemma":0.06700441,"domain_scores_codex":[0.9989523,0.0001364317,0.0001905893,0.000315149,0.00024714,0.0001584472],"domain_scores_gemma":[0.9958565,0.0006229833,0.0005924931,0.0003813743,0.002318476,0.0002282035],"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":[0.00002048597,0.000009243098,0.0009865465,0.0002749473,0.00002123448,0.000006523564,0.00001131642,0.00009420555,0.00001693756,0.0002921489,0.997038,0.00122839],"study_design_scores_gemma":[0.0002358951,0.00001632226,0.01158332,0.0005114467,0.00006581912,0.00004533719,0.0002399776,0.0003595242,0.0001345631,0.001148135,0.9856237,0.0000360585],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008398625,0.00004512077,0.00003309788,0.0000780457,0.00003255834,0.000007276751,0.9991533,0.00005769913,0.0005089335],"genre_scores_gemma":[0.00055856,0.0001155657,0.0001744892,0.00007716059,0.0000206415,0.00009378794,0.9979336,0.00005086699,0.0009752715],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07645077,"threshold_uncertainty_score":0.2557533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04441688778890846,"score_gpt":0.2499884822148569,"score_spread":0.2055715944259485,"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."}}