{"id":"W3089140438","doi":"10.1186/s40795-020-00378-z","title":"Modeling the predictors of stunting in Ethiopia: analysis of 2016 Ethiopian demographic health survey data (EDHS)","year":2020,"lang":"en","type":"article","venue":"BMC Nutrition","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Medicine; Multicollinearity; Clinical nutrition; Confidence interval; Odds ratio; Demography; Logistic regression; Socioeconomic status; Environmental health; Confounding; Malnutrition; Public health; Odds; Descriptive statistics; Regression analysis; Population; Statistics","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":[0.00170596,0.0001377513,0.0005038029,0.0005015765,0.00009721587,0.00003046817,0.0005431406,0.0001148524,0.00001001826],"category_scores_gemma":[0.0003612691,0.0001172047,0.0001441615,0.002527766,0.00007055303,0.0002743362,0.0001325527,0.0003185481,8.449881e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002984461,"about_ca_system_score_gemma":0.00004132278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004031633,"about_ca_topic_score_gemma":0.009915471,"domain_scores_codex":[0.9973351,0.000833046,0.0008411315,0.0003964057,0.0003619069,0.0002323676],"domain_scores_gemma":[0.9986469,0.0003095121,0.0002865707,0.0005323827,0.0001413128,0.00008329017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00076997,0.000647523,0.9849826,0.001263297,0.0002546624,7.429309e-7,0.002690393,0.007130415,0.0005991322,0.00004780196,0.001147566,0.0004659751],"study_design_scores_gemma":[0.00280052,0.0001863808,0.5717101,0.0008493386,0.0003866389,8.59622e-7,0.0007366595,0.4217885,0.0009801846,0.0002359014,0.00009941009,0.0002255573],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859312,0.001349508,0.006200628,0.004893244,0.0001811779,0.0005878187,0.0007928286,0.00004779014,0.00001584806],"genre_scores_gemma":[0.9968226,0.0003847888,0.0005223755,0.0005511849,0.0001323072,0.000008590388,0.001560384,0.00001700259,7.476604e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4146581,"threshold_uncertainty_score":0.6094649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1091498770690793,"score_gpt":0.3371706731850928,"score_spread":0.2280207961160135,"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."}}