{"id":"W6938949752","doi":"10.6068/dp1690c7b0bbe39","title":"TREND: Foreign Agricultural Service, United States Department of Agriculture. World Agricultural Production, Supply, and Distribution: Agricultural Commodities | Country: Canada | Commodity: Sugar, Centrifugal | Attribute: Production, 1960 - 2019. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 008-007-001","year":2019,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Commodity; Agricultural communication; Agricultural productivity; Agricultural marketing; Good agricultural practice; Agricultural 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":[0.001067254,0.001647664,0.001523144,0.004052967,0.0009320764,0.002545814,0.002957152,0.001489907,0.06932833],"category_scores_gemma":[0.006712947,0.0007453387,0.001015524,0.01445184,0.0004592903,0.002040847,0.001500833,0.002708391,0.08418176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003354317,"about_ca_system_score_gemma":0.006739874,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1967075,"about_ca_topic_score_gemma":0.2040436,"domain_scores_codex":[0.9989635,0.0001137196,0.0001304698,0.0003055898,0.0003043195,0.0001824494],"domain_scores_gemma":[0.9956456,0.0005106095,0.0005148948,0.0006284863,0.002304624,0.000395848],"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":[0.00001942445,0.000008507021,0.0006013834,0.0002133117,0.00001431076,0.000005463093,0.000007703946,0.00009485206,0.00001998587,0.0002096622,0.9978442,0.0009610372],"study_design_scores_gemma":[0.0001631614,0.00001144113,0.006329181,0.0003345431,0.00002811226,0.00002294985,0.0001105671,0.0002930921,0.0001325432,0.0007865845,0.9917606,0.00002721983],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003052263,0.00002183469,0.00001499939,0.00003651492,0.00001279337,0.000003862389,0.9995893,0.00004390395,0.0002461947],"genre_scores_gemma":[0.000194851,0.00005047343,0.0001028212,0.00003047372,0.000005970236,0.00003876123,0.9991131,0.0000264599,0.0004370387],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8032925,"threshold_uncertainty_score":0.3911251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01657461867065682,"score_gpt":0.2205118537763019,"score_spread":0.203937235105645,"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."}}