{"id":"W3164089634","doi":"10.1111/mcn.13205","title":"Cut‐off points for serum ferritin to identify low iron stores during the first year of life in a cohort of Mexican infants","year":2021,"lang":"en","type":"article","venue":"Maternal and Child Nutrition","topic":"Iron Metabolism and Disorders","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nutrition International","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Medicine; Ferritin; Iron deficiency; Iron status; Cohort; Pediatrics; Cluster (spacecraft); Iron supplement; Serum ferritin; Cohort study; Birth weight; Iron supplementation; Demography; Anemia; Internal medicine; Pregnancy","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":[0.0008812803,0.0003879594,0.0003166889,0.0007480059,0.0003954473,0.0006252617,0.000342346,0.0003710289,0.0006865112],"category_scores_gemma":[0.002295532,0.0001996115,0.0004150718,0.0003927776,0.0001907635,0.0002256172,0.0003914573,0.0004196647,0.0001258579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002598765,"about_ca_system_score_gemma":0.0002390036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005035155,"about_ca_topic_score_gemma":0.003999011,"domain_scores_codex":[0.9996977,0.00008509361,0.00002525742,0.00007266263,0.00005038097,0.00006887753],"domain_scores_gemma":[0.9992506,0.0001362518,0.000343712,0.00007212075,0.0000911571,0.0001061747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002066495,0.0000350876,0.9970367,0.000006446699,0.00002222284,0.00008167305,0.0001568309,0.0000180076,0.0005783773,0.00001693681,0.00006784249,0.001773181],"study_design_scores_gemma":[0.000005916277,0.0001195417,0.9987777,0.000008723284,0.0000161187,0.0002440902,0.0003663575,0.0001735586,0.0001085303,0.00001946125,0.000157411,0.00000250334],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996518,0.0000782679,0.00008197971,0.00001325173,0.000002694409,0.000004497924,0.00006658995,0.000001692409,0.00009920122],"genre_scores_gemma":[0.9994119,0.00005368692,0.0001790285,0.00001223853,0.000003684899,0.00001301714,0.0002185536,0.000001940384,0.0001058926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005035155,"threshold_uncertainty_score":0.01001173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004957875609632239,"score_gpt":0.2396793039683335,"score_spread":0.2347214283587013,"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."}}