{"id":"W6958041095","doi":"10.6068/dp15e7079326f17","title":"Trend 1963 - 2015. Food and Agriculture Organization of the United Nations. Food and Agriculture Organization Statistics: Forestry | Country: Canada | Item: Particle Board | Element: Import Value - 1000 US$, 1963-2015. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 067-001-004.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; European union; General partnership; Commission; Food security; Value (mathematics); International comparisons; Food processing","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":[0.001645061,0.001875711,0.001798563,0.00597548,0.001112771,0.003166215,0.003061227,0.001095492,0.08748261],"category_scores_gemma":[0.01091069,0.001126125,0.001255356,0.02900996,0.0004022894,0.002777662,0.001670577,0.002569868,0.07709341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008113419,"about_ca_system_score_gemma":0.01960632,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.720794,"about_ca_topic_score_gemma":0.6210381,"domain_scores_codex":[0.9977193,0.0001737892,0.0002890343,0.0003629144,0.00105915,0.0003957434],"domain_scores_gemma":[0.9894349,0.0007256498,0.0008038756,0.000657206,0.007877083,0.0005014046],"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":[0.00001904043,0.000007298523,0.0006974389,0.0002209206,0.00001397744,0.000005114796,0.000009331705,0.00009217021,0.00001152844,0.0003092359,0.9972091,0.001404852],"study_design_scores_gemma":[0.00009993021,0.00001066405,0.01439222,0.0005397819,0.00002980394,0.00001664944,0.0001742214,0.0002006286,0.0001357051,0.0005881498,0.9837776,0.00003464487],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003485744,0.00002992391,0.00001695893,0.00004216045,0.00002682715,0.00000767135,0.9992108,0.00003180793,0.0005989269],"genre_scores_gemma":[0.0002941636,0.0001083474,0.0001383142,0.00003964684,0.00001138509,0.00006296636,0.9979287,0.00004455617,0.001371837],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.279206,"threshold_uncertainty_score":0.5617006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01491016024958939,"score_gpt":0.2180758515480796,"score_spread":0.2031656912984902,"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."}}