{"id":"W6976325356","doi":"10.6068/dp14ba879e95581","title":"Trend 1976 - 2009. Statistics Canada. CANSIM: Agriculture - Livestock and Aquaculture | Country: Canada | Table: Nutrients in the food supply, by source of nutritional equivalent and commodity | Variable: Standard milk 3.25%, Fatty acids, mono-unsaturated, Nutrients available | Units: Milligrams Grams, 1976-2009. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-007.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Livestock; Agriculture; Economic statistics; Census; Commodity; Official statistics; Statistical analysis; Socioeconomic status","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":[0.002047087,0.002474975,0.002676849,0.007998729,0.003127104,0.004370336,0.005207735,0.001534043,0.1041114],"category_scores_gemma":[0.01689667,0.001704868,0.002303803,0.0405913,0.0006807795,0.002455043,0.00216245,0.00295537,0.05588209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05302312,"about_ca_system_score_gemma":0.1380709,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9945177,"about_ca_topic_score_gemma":0.9924445,"domain_scores_codex":[0.9962627,0.0002343626,0.0004204851,0.0005064611,0.001807724,0.0007681586],"domain_scores_gemma":[0.9678512,0.001127994,0.0009296071,0.0008730735,0.02783242,0.001385675],"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":[0.00002700274,0.000006425218,0.001052825,0.000332272,0.00002525601,0.000006465769,0.00001953903,0.000114465,0.0000125055,0.0003973189,0.9962015,0.001804504],"study_design_scores_gemma":[0.0001536199,0.00001194291,0.02212587,0.0009368476,0.0000759225,0.00002432818,0.0003538452,0.0003819945,0.0001756051,0.0006787595,0.9749975,0.00008383435],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004168865,0.00005428277,0.00002188421,0.0001023151,0.00002514631,0.00001344079,0.9988685,0.00004712096,0.000825603],"genre_scores_gemma":[0.0008515233,0.0004014706,0.0004574854,0.0001758233,0.00001835804,0.0001379526,0.993434,0.0001167385,0.004406694],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1041114,"threshold_uncertainty_score":0.3847114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02258942064760283,"score_gpt":0.2312560470523552,"score_spread":0.2086666264047524,"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."}}