{"id":"W6901589280","doi":"10.6068/dp14ba8130ca442","title":"Trend 1976 - 2009. Statistics Canada. CANSIM: Agriculture - Food and Nutrition | Country: Canada | Table: Nutrients in the food supply, by source of nutritional equivalent and commodity | Variable: Beef and veal, total, Iron, Nutrients available | Units: Milligrams, 1976-2009. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-005.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Economic statistics; Census; Commodity; Food security; Official statistics; Summary statistics; Food supply","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002303942,0.002446463,0.002894538,0.008426322,0.00340539,0.004912561,0.005278682,0.001541919,0.120481],"category_scores_gemma":[0.01837147,0.001810144,0.00236545,0.0439599,0.0006977265,0.002716827,0.002408705,0.003159761,0.06755572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05945797,"about_ca_system_score_gemma":0.1530178,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946969,"about_ca_topic_score_gemma":0.9921633,"domain_scores_codex":[0.9956048,0.0003148775,0.000491364,0.0005690733,0.002056269,0.000963753],"domain_scores_gemma":[0.9636895,0.001365593,0.001030142,0.001082223,0.03120263,0.001629836],"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":[0.00002793748,0.000006546613,0.0009334935,0.0003152774,0.00002390114,0.000006441989,0.00002102704,0.0001064251,0.00001175418,0.000430503,0.9961336,0.001983053],"study_design_scores_gemma":[0.0001394963,0.00001213994,0.01965081,0.0008860529,0.00007179962,0.00002496815,0.0003864556,0.000360636,0.0001656886,0.0006907171,0.9775278,0.00008355019],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004411947,0.00006305163,0.00002817948,0.000125974,0.00003298024,0.0000173014,0.9985332,0.00006104655,0.001094022],"genre_scores_gemma":[0.0009337497,0.0004736293,0.0005560283,0.0002100369,0.00002190209,0.0001649199,0.9917006,0.0001549298,0.005784184],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.879519,"threshold_uncertainty_score":0.4313998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0218000272279806,"score_gpt":0.2267551328958551,"score_spread":0.2049551056678745,"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."}}