{"id":"W3212081173","doi":"10.1093/cdn/nzab130","title":"Age-Based Anthropometric Cutoffs Provide Inconsistent Estimates of Undernutrition: Findings from a Cross-Sectional Assessment of Late-Adolescent and Young Women in Rural Pakistan","year":2021,"lang":"en","type":"article","venue":"Current Developments in Nutrition","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"World Food Prize Foundation; Bill and Melinda Gates Foundation","keywords":"Anthropometry; Demography; Cross-sectional study; Malnutrition; Medicine; Young adult; Pediatrics; Gerontology; Internal medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003473089,0.0002459969,0.0004870762,0.000901852,0.00009765788,0.0001282464,0.0001362728,0.0001303345,0.00005312136],"category_scores_gemma":[0.00009459913,0.0002815383,0.00007651823,0.001135543,0.0001934949,0.0003026268,0.00009317297,0.0002918426,9.16348e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00123997,"about_ca_system_score_gemma":0.0001527593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001123832,"about_ca_topic_score_gemma":0.000102354,"domain_scores_codex":[0.9973993,0.0001341438,0.001093772,0.0004582226,0.0005228242,0.0003917474],"domain_scores_gemma":[0.9991192,0.000132923,0.0002430521,0.0001624884,0.0002351244,0.0001072003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003312901,0.003890166,0.9889417,0.00184056,0.00002310549,0.00001780295,0.0003608666,0.00002052378,0.003525718,0.00003912794,0.00004772138,0.000961454],"study_design_scores_gemma":[0.008174201,0.00009390462,0.9576844,0.00323788,0.00001206463,0.000008011553,0.0002517054,0.0004802019,0.02667162,0.002962462,0.0001478371,0.0002757267],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966747,0.001126517,0.0002822648,0.000146399,0.0008932545,0.0006213307,0.0001777411,0.00003084693,0.00004699959],"genre_scores_gemma":[0.9939623,0.0003988706,0.0044259,0.00003638091,0.00003911851,0.0001435329,0.0009691383,0.00002059228,0.000004161916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03125728,"threshold_uncertainty_score":0.9999637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03251084754936569,"score_gpt":0.3548529659969021,"score_spread":0.3223421184475365,"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."}}