{"id":"W2947695528","doi":"10.1111/mcn.12812","title":"Integrating nutrition outcomes into agriculture development for impact at scale: Highlights from the Canadian International Food Security Research Fund","year":2019,"lang":"en","type":"article","venue":"Maternal and Child Nutrition","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Saint Vincent University; University of British Columbia; Agriculture and Agri-Food Canada; International Development Research Centre","funders":"Global Affairs Canada; International Development Research Centre","keywords":"Medicine; Food security; Agriculture; Scale (ratio); Economic growth; Environmental health; Agricultural economics; Environmental resource management; Environmental science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002781869,0.0002271932,0.0002229834,0.000186719,0.001123561,0.0005416897,0.0003130834,0.0001701437,0.0001311306],"category_scores_gemma":[0.00001939947,0.0001440565,0.0001042536,0.0001480716,0.00006283481,0.0003206269,0.00009414456,0.0003292492,0.00004259398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007116263,"about_ca_system_score_gemma":0.00002090319,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02547405,"about_ca_topic_score_gemma":0.188568,"domain_scores_codex":[0.9983166,0.0001101383,0.0003245398,0.0004086529,0.0004478471,0.0003921741],"domain_scores_gemma":[0.9991742,0.0001268056,0.00008794774,0.0001632862,0.0002571643,0.0001906237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00402609,0.001650025,0.9063901,0.001294965,0.0005241024,0.00001232144,0.01081598,0.000003428321,0.005994965,0.002553203,0.06265179,0.004083035],"study_design_scores_gemma":[0.006057627,0.0005253733,0.6799964,0.001636032,0.00003367087,0.00006156355,0.0004382026,0.0001091759,0.09597589,0.01994226,0.1947418,0.0004819787],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9719175,0.0004545453,0.000008265319,0.02452173,0.0008662157,0.001301823,0.0004696009,0.00004994706,0.0004103605],"genre_scores_gemma":[0.9966304,0.00006271168,0.000365125,0.0006487963,0.0008255496,0.0001861502,0.001182658,0.00002203515,0.00007658536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2263937,"threshold_uncertainty_score":0.9810154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02024926047031466,"score_gpt":0.2964883985430694,"score_spread":0.2762391380727547,"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."}}