{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006689776,0.0009746645,0.0006947013,0.001501855,0.0003882874,0.001185099,0.000832378,0.0004686684,0.00142387],"category_scores_gemma":[0.00793953,0.0005844535,0.001748403,0.001266833,0.0002376958,0.0004608257,0.0008038867,0.001043145,0.0002578957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001045132,"about_ca_system_score_gemma":0.002180884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03451129,"about_ca_topic_score_gemma":0.02119029,"domain_scores_codex":[0.9980161,0.001344001,0.0001023168,0.0002458564,0.0001132532,0.0001784382],"domain_scores_gemma":[0.9941502,0.004496092,0.000625069,0.000179362,0.0003461008,0.0002033737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002172994,0.0002013677,0.9358444,0.000129822,0.0009020416,0.0002599052,0.0002508159,0.05006478,0.0001498123,0.0005965719,0.001427545,0.009955709],"study_design_scores_gemma":[0.00007104099,0.000520076,0.3853607,0.0003068296,0.0006018445,0.0004450215,0.001552324,0.6048857,0.000429478,0.002153592,0.003612774,0.00006067969],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845238,0.0007923619,0.008130718,0.0007011527,0.0000492286,0.000117465,0.004977935,0.00007500068,0.0006323945],"genre_scores_gemma":[0.9853684,0.0005125941,0.009765771,0.00008491683,0.00002788774,0.0001355842,0.00361812,0.00001375479,0.0004730342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03451129,"threshold_uncertainty_score":0.06862086,"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."}}