{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01985335,0.001753575,0.001300425,0.001269376,0.0006355718,0.001116451,0.00233502,0.001094817,0.002106035],"category_scores_gemma":[0.06269581,0.0006503787,0.00391379,0.002502839,0.0008997635,0.0008847513,0.001419225,0.001064781,0.0002956289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001020436,"about_ca_system_score_gemma":0.002416388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07202581,"about_ca_topic_score_gemma":0.03907671,"domain_scores_codex":[0.9750859,0.017186,0.001260595,0.004554354,0.001019266,0.000893893],"domain_scores_gemma":[0.9634638,0.02314469,0.005066717,0.005666404,0.001779981,0.0008783914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00107197,0.00005920873,0.9771111,0.0003683961,0.004120703,0.0001279545,0.0003288754,0.001649139,0.0007718972,0.0003853613,0.0006904694,0.01331486],"study_design_scores_gemma":[0.0000603491,0.001190194,0.9829363,0.0001948678,0.003141381,0.0002579792,0.0003966595,0.007415966,0.001285767,0.000372393,0.002717053,0.0000311969],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9560413,0.005049558,0.02750907,0.001110309,0.0006294947,0.000274424,0.006651355,0.0003877158,0.002346808],"genre_scores_gemma":[0.9906709,0.0002915105,0.007146434,0.0001629342,0.00002646195,0.0001391984,0.0010469,0.00006148235,0.000454154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07202581,"threshold_uncertainty_score":0.1432132,"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."}}