{"id":"W6976617642","doi":"10.6068/dp15df469845670","title":"Trend 1997 - 2014. Food and Agriculture Organization of the United Nations. Food and Agriculture Organization Statistics: Investment - Credit to Agriculture | Country: Canada | Item: Total Credit | Element: Value Local Currency - millions, 1997-2014. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 067-001-071.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"Trypanosoma species research and implications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Index (typography); Currency; Investment (military); European union; Food security; Official statistics","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":[0.00141915,0.001715521,0.001695367,0.005279395,0.001008029,0.003025307,0.002803396,0.001142364,0.0703627],"category_scores_gemma":[0.01058651,0.001034485,0.001097037,0.02232147,0.0003692095,0.002598685,0.001700165,0.002558161,0.06611391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005512865,"about_ca_system_score_gemma":0.0118496,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5131076,"about_ca_topic_score_gemma":0.4404845,"domain_scores_codex":[0.998063,0.000178514,0.0002437184,0.0003796089,0.0007775297,0.0003576623],"domain_scores_gemma":[0.9900941,0.000781364,0.0008763573,0.0006058089,0.007166559,0.0004757997],"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":[0.00001745249,0.000007933727,0.0009720132,0.0001891222,0.0000140535,0.0000052955,0.000009524594,0.00008423597,0.00001076399,0.0002977106,0.9971402,0.00125175],"study_design_scores_gemma":[0.00011675,0.00001190403,0.01617119,0.0005523255,0.00003180671,0.00001908595,0.0002078706,0.0002506458,0.0001342226,0.0006367564,0.9818326,0.00003480156],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004751793,0.00002639636,0.00001702071,0.00004729951,0.00002289889,0.000007315638,0.999276,0.00002652855,0.0005290074],"genre_scores_gemma":[0.0002752241,0.00008142573,0.0001161963,0.00003881477,0.00001065445,0.00007021285,0.9983448,0.00003065202,0.001032071],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4868924,"threshold_uncertainty_score":0.9795196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01583633724264803,"score_gpt":0.2524448278661132,"score_spread":0.2366084906234652,"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."}}