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Record W2756915546 · doi:10.1097/mpg.0000000000001761

Iron Status in Pediatric Celiac Disease

2017· article· en· W2756915546 on OpenAlexaff
Jelena Popov, Mina Baldawi, Lawrence Mbuagbaw, Michelle Gould, Heather Mileski, Herbert Brill, Nikhil Pai

Bibliographic record

VenueJournal of Pediatric Gastroenterology and Nutrition · 2017
Typearticle
Languageen
FieldMedicine
TopicCeliac Disease Research and Management
Canadian institutionsSt. Joseph’s Healthcare HamiltonUniversity of TorontoMcMaster University
Fundersnot available
KeywordsMedicineTissue transglutaminaseFerritinGastroenterologySerum ferritinBiomarkerRetrospective cohort studyDiseaseGluten freeInternal medicineIron deficiencyPathologyAnemiaBiochemistryEnzyme

Abstract

fetched live from OpenAlex

The present study assessed the role of serum ferritin as a noninvasive biomarker in the diagnosis and monitoring of pediatric celiac disease. A retrospective chart review was performed on patients younger than 18 years old at time of diagnosis (n = 193) between 1998 and 2015. A total of 653 paired values demonstrated a weak negative correlation between serum ferritin and tissue transglutaminase-immunoglobulin A (r = -0.114; P = 0.004), necessitating further evaluation. A significant relationship was found between reduction of tissue transglutaminase-immunoglobulin A and increase in serum ferritin after institution of a gluten-free diet (P < 0.0001), suggesting that resolution of villous damage is necessary for promoting adequate iron absorption.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.290
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2017
Admission routes1
Has abstractyes

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