{"id":"W2515120013","doi":"10.1007/s10995-016-2173-z","title":"Malnutrition in Pre-school Children across Different Geographic Areas and Socio-Demographic Groups in Ghana","year":2016,"lang":"en","type":"article","venue":"Maternal and Child Health Journal","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Michael's Hospital; McMaster University","funders":"","keywords":"Malnutrition; Underweight; Medicine; Psychological intervention; Logistic regression; Environmental health; Public health; Population; Socioeconomic status; Malnutrition in children; Demography; Pediatrics; Gerontology; Overweight; Obesity; Nursing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005189688,0.0002566433,0.000402619,0.0004629209,0.0004433963,0.0002327753,0.0001578242,0.0001270717,0.00004715193],"category_scores_gemma":[0.00001301711,0.0001733521,0.00008829724,0.0001773328,0.0001177874,0.0003793956,0.00007298626,0.0005948844,0.000002539476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001146037,"about_ca_system_score_gemma":0.00001030396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005419773,"about_ca_topic_score_gemma":0.0007113519,"domain_scores_codex":[0.9977782,0.0002263527,0.0006793732,0.0003521478,0.0002735561,0.000690362],"domain_scores_gemma":[0.9991333,0.00003594964,0.0002300887,0.0001163381,0.00003033476,0.0004539951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005345616,0.0001802454,0.9882261,0.0001514074,0.00001383383,0.00001662834,0.0005204405,1.912623e-7,0.00002669565,0.00002181883,0.00006806218,0.01024004],"study_design_scores_gemma":[0.006365725,0.0002521056,0.9843043,0.00250053,0.000006992967,0.001233473,0.00006305652,0.000007258251,0.0001571339,0.004847862,0.00004828383,0.0002132942],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9713689,0.003430137,0.00003720862,0.02441465,0.0002877839,0.000365843,0.00005319396,0.00003171501,0.00001057132],"genre_scores_gemma":[0.9921862,0.005439768,0.00003284572,0.001795086,0.0004888994,0.00001356176,0.000008035339,0.00002518428,0.00001039383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02261956,"threshold_uncertainty_score":0.7069095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00833472113048436,"score_gpt":0.2681253385940285,"score_spread":0.2597906174635441,"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."}}