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Record W4408454437 · doi:10.14309/ajg.0000000000003400

Assessing Mucosal Recovery During the First 15 Months of Adopting a Gluten-Free Diet in Children With Celiac Disease

2025· article· en· W4408454437 on OpenAlexaffabout
Denis Chang, Madison Wong, Cleo R. Davidowitz, Imad Absah, Vahe Badalyan, Mohammad Karam Chaaban, Lisa M. Fahey, Daniela Migliarese Isaac, Marihan Lansing, Edwin Liu, Catherine Raber, Arunjot Singh, Marisa G. Stahl, Catharine M. Walsh, Jocelyn A. Silvester, Maureen M. Leonard

Bibliographic record

VenueThe American Journal of Gastroenterology · 2025
Typearticle
Languageen
FieldMedicine
TopicCeliac Disease Research and Management
Canadian institutionsSickKids FoundationUniversity of TorontoThe Wilson CentreHospital for Sick ChildrenStollery Children's Hospital
FundersDivision of Diabetes, Endocrinology, and Metabolic DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesTakeda Pharmaceuticals U.S.A.
KeywordsMedicineEnteropathyDiseaseRetrospective cohort studyGluten freeProtein losing enteropathyBiopsyCohortInternal medicineGlutenCohort studyGastroenterologyPediatricsSurgeryPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Determine contemporary rates of early mucosal recovery in children with celiac disease (CeD). METHODS: Multicenter retrospective cohort study in Canada and the United States. Children diagnosed with CeD between 2016 and 2021 who underwent a follow-up biopsy within 15 months of diagnosis were included. RESULTS: Overall, 96 of 130 children (74%) had mucosal recovery, including 48% children (12/25) who were assessed within 3 months. Musculoskeletal symptoms at diagnosis were the only clinical characteristic associated with persistent enteropathy. DISCUSSION: While mucosal recovery can occur within months, more than a quarter of children with CeD had persistent enteropathy within 15 months of treatment.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.260
Teacher spread0.254 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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