{"id":"W2758262453","doi":"10.5376/ijh.2017.07.0024","title":"Development of Vegetable Nutrition Garden Model For Diet Diversification and Improved Nutrition Security of Urban and Peri-urban Households","year":2017,"lang":"en","type":"article","venue":"International Journal of Horticulture","topic":"Urban Agriculture and Sustainability","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diversification (marketing strategy); Malnutrition; Nutrient; Food security; Forest gardening; Business; Biotechnology; Agroforestry; Agriculture; Biology; Economics; Economic growth; Ecology; Marketing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002082269,0.00009392652,0.0001941515,0.00001358995,0.000167697,0.00007339005,0.0002394787,0.00009315574,0.000004723126],"category_scores_gemma":[0.0001087223,0.00004031264,0.00008645211,0.00002475701,0.0000839042,0.0003222497,0.00006297936,0.00008267832,6.103572e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004849176,"about_ca_system_score_gemma":0.00001838463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001958105,"about_ca_topic_score_gemma":0.0001613887,"domain_scores_codex":[0.9991608,0.00001681541,0.0003698234,0.000130315,0.0002285558,0.00009369089],"domain_scores_gemma":[0.9983858,0.00003355203,0.0005626511,0.00003668673,0.0009202335,0.0000610883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001735309,0.001738324,0.04326177,0.0003642338,0.0003602781,0.00000583511,0.009554989,0.00001383152,0.9284614,0.0009433873,0.006505977,0.00705464],"study_design_scores_gemma":[0.004736896,0.001903331,0.8348803,0.0006729235,0.0003189485,0.00006966112,0.01298296,0.00566663,0.09192731,0.006528765,0.03965041,0.000661883],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981062,0.0005140326,0.00005544891,0.0008353777,0.00007105491,0.0002564383,0.00009902781,0.000004179855,0.00005819108],"genre_scores_gemma":[0.9979272,0.0001560743,0.001586189,0.00001351642,0.0002051668,0.00001134688,0.00003769446,7.766857e-7,0.00006199606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8365341,"threshold_uncertainty_score":0.1643902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01846954259235581,"score_gpt":0.2355926447512432,"score_spread":0.2171231021588874,"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."}}