{"id":"W6939186084","doi":"10.6068/dp14ba84dd0a439","title":"Trend 1988 - 2009. Statistics Canada. CANSIM: Agriculture - Livestock and Aquaculture | Country: Canada | Table: Nutrients in the food supply, by source of nutritional equivalent and commodity | Variable: Papayas, Vitamin K, Nutrients available adjusted for losses | Units: Micrograms, 1988-2009. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-007.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","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":[0.001815944,0.002253162,0.002605252,0.007553984,0.002894058,0.003877536,0.004913512,0.001454601,0.08717303],"category_scores_gemma":[0.013836,0.00168604,0.002205962,0.03763423,0.0006204164,0.002220188,0.002037678,0.002910351,0.04218888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05779503,"about_ca_system_score_gemma":0.1445429,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9957165,"about_ca_topic_score_gemma":0.994002,"domain_scores_codex":[0.9963967,0.0002150399,0.0004084462,0.0004452225,0.001737413,0.0007971746],"domain_scores_gemma":[0.9735603,0.000834532,0.0008892904,0.0006355582,0.02285295,0.001227347],"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":[0.00003297943,0.000007653027,0.001374702,0.0003732935,0.00002881792,0.000007968772,0.00002179302,0.0001174749,0.00001264363,0.0004079369,0.9957315,0.00188323],"study_design_scores_gemma":[0.000182352,0.00001622905,0.03364718,0.001086554,0.00009548736,0.00003292561,0.0004825948,0.0004176603,0.0001935133,0.0006223678,0.9631379,0.00008528827],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006322093,0.00007295014,0.00002117,0.0001416084,0.00002980626,0.00001592321,0.998632,0.0000415189,0.0009817324],"genre_scores_gemma":[0.001376775,0.0005995007,0.0004937372,0.0002493786,0.00002300011,0.0001714122,0.9905475,0.0001056905,0.006432995],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08717303,"threshold_uncertainty_score":0.4193343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02366413875476939,"score_gpt":0.2192816202945405,"score_spread":0.1956174815397711,"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."}}