{"id":"W6920400396","doi":"10.6068/dp14ba84a5f995","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: Strawberries, Riboflavin, Nutrients available adjusted for losses | 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; Official statistics; Commodity; Food security; 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":[],"consensus_categories":[],"category_scores_codex":[0.002163045,0.002464684,0.002766914,0.008051375,0.003090492,0.004462642,0.005088525,0.001571983,0.119555],"category_scores_gemma":[0.01665392,0.001713294,0.002325784,0.04197328,0.0006450225,0.002512372,0.002297629,0.00303024,0.06601912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05107644,"about_ca_system_score_gemma":0.1306154,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9931446,"about_ca_topic_score_gemma":0.9902605,"domain_scores_codex":[0.9961262,0.0002818458,0.0004421859,0.0005340311,0.001767081,0.0008486044],"domain_scores_gemma":[0.9689876,0.001223227,0.0009860379,0.0009733892,0.0264398,0.001389954],"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":[0.00002899997,0.000006346392,0.0009439591,0.0003359181,0.00002593038,0.000006541145,0.00001962953,0.0001054927,0.00001274526,0.0003989767,0.9962426,0.001872858],"study_design_scores_gemma":[0.0001524817,0.00001222647,0.02072008,0.0009003354,0.00007462993,0.00002498395,0.0003386201,0.0003482985,0.0001678599,0.0006748,0.9765034,0.00008216249],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003879283,0.00005348007,0.00002403697,0.0001009651,0.00002640318,0.00001400056,0.9988309,0.00005108032,0.0008602788],"genre_scores_gemma":[0.0007862232,0.0003847228,0.0004597297,0.0001743347,0.00001861254,0.0001437275,0.9934288,0.000127706,0.004476107],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.119555,"threshold_uncertainty_score":0.3999513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02942855507229718,"score_gpt":0.2381615570944327,"score_spread":0.2087330020221355,"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."}}