{"id":"W2260295510","doi":"10.1111/mcn.12245","title":"Constraints and opportunities for implementing nutrition‐specific, agricultural and market‐based approaches to improve nutrient intake adequacy among infants and young children in two regions of rural Kenya","year":2015,"lang":"en","type":"article","venue":"Maternal and Child Nutrition","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"NutriAg (Canada)","funders":"United States Agency for International Development","keywords":"Psychological intervention; Context (archaeology); Environmental health; Medicine; Nutrient; Kenya; Agriculture; Nutrient density; Productivity; Leafy vegetables; Food science; Economic growth; Economics; Geography; Ecology; Nursing; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003089268,0.000395849,0.000491293,0.0004830749,0.003579483,0.001461836,0.0007888433,0.0006827732,0.001666853],"category_scores_gemma":[0.005960085,0.0005652334,0.0002922464,0.0007803051,0.001330943,0.0008175923,0.001900069,0.0007825822,0.00008919814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003992219,"about_ca_system_score_gemma":0.009200867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07638909,"about_ca_topic_score_gemma":0.2067193,"domain_scores_codex":[0.9976881,0.001109448,0.00016942,0.0001165281,0.0001884751,0.0007281029],"domain_scores_gemma":[0.9972501,0.001175338,0.0008504507,0.00004969603,0.0001905134,0.0004837944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001048255,0.001345705,0.4517085,0.002688941,0.0001394007,0.007315918,0.4364413,0.001122674,0.008512734,0.00281995,0.0009212017,0.08593543],"study_design_scores_gemma":[0.0001190088,0.001990064,0.5784767,0.0009951774,0.0001670742,0.001013917,0.4082286,0.0006439512,0.001147826,0.0004106277,0.006733088,0.00007391451],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983993,0.0002307922,0.0000585642,0.0002706192,0.000001703023,0.00007027798,0.00002746066,0.000001602566,0.000939612],"genre_scores_gemma":[0.9979917,0.0006107774,0.0007623394,0.0001069709,0.000001979395,0.0001801334,0.00002780363,0.000001630882,0.0003165392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07638909,"threshold_uncertainty_score":0.1518889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05354794868578077,"score_gpt":0.2556379883082099,"score_spread":0.2020900396224291,"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."}}