{"id":"W2787152173","doi":"10.1186/s12982-018-0070-1","title":"Effect of correcting for gestational age at birth on population prevalence of early childhood undernutrition","year":2018,"lang":"en","type":"article","venue":"Emerging Themes in Epidemiology","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; Institute for Clinical Evaluative Sciences; Public Health Ontario; University of Toronto","funders":"Wellcome Trust","keywords":"Medicine; Gestational age; Odds ratio; Small for gestational age; Confidence interval; Birth weight; Population; Pediatrics; Malnutrition; Low birth weight; Obstetrics; Epidemiology; Pregnancy; Demography; Internal medicine; Environmental health","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":[0.001469527,0.0001317149,0.0003989421,0.000225145,0.00009282861,0.000002210067,0.0001336898,0.0001037108,0.00003259048],"category_scores_gemma":[0.002341299,0.000119306,0.000108584,0.0001487307,0.0001253513,0.00007952311,0.00003415353,0.0001062209,0.000002442415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008254724,"about_ca_system_score_gemma":0.000003585397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001301807,"about_ca_topic_score_gemma":0.00003730146,"domain_scores_codex":[0.9980541,0.0007159945,0.0006091003,0.000283548,0.00009269282,0.0002446056],"domain_scores_gemma":[0.9954018,0.003956213,0.0003871316,0.000169251,0.00005786316,0.00002775645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002341112,0.0001749208,0.9809856,0.0008511888,0.00002198044,4.455965e-7,0.001640412,0.0003805961,0.001037392,0.001228729,0.0004835841,0.01085407],"study_design_scores_gemma":[0.002061047,0.002372785,0.945084,0.0006004415,0.00002767392,0.000006795798,0.00001550252,0.001461796,0.03088085,0.01725879,0.00009374008,0.000136584],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996835,0.0001369164,0.0009445929,0.0006393849,0.0007591881,0.0005058383,0.00003009122,0.00003585498,0.0001131139],"genre_scores_gemma":[0.9984419,0.00001490453,0.0009534603,0.0001847908,0.0002469229,0.00003352264,0.00006978628,0.0000186593,0.00003609623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03590158,"threshold_uncertainty_score":0.4865158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03194461130878601,"score_gpt":0.3591378827952172,"score_spread":0.3271932714864312,"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."}}