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Record W2074150127 · doi:10.1155/2014/293206

Gluten Sensitivity Presenting as a Neuropsychiatric Disorder

2014· review· en· W2074150127 on OpenAlexaff
Stephen J. Genuis, Rebecca A. Lobo

Bibliographic record

VenueGastroenterology Research and Practice · 2014
Typereview
Languageen
FieldMedicine
TopicCeliac Disease Research and Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineGlutenEtiologyAutismAtaxiaDiseaseGluten freeClinical PracticeIntensive care medicinePsychiatryPediatricsDermatologyGastroenterologyInternal medicinePathologyPhysical therapy

Abstract

fetched live from OpenAlex

There has been increasing recognition in the medical community and the general public of the widespread prevalence of gluten sensitivity. Celiac disease (CD) was initially believed to be the sole source of this phenomenon. Signs and symptoms indicative of nonceliac gluten sensitivity (NCGS), in which classical serum and intestinal findings of CD may be absent, have been frequently reported of late. Clinical manifestations in patients with NCGS are characteristically triggered by gluten and are ameliorated or resolved within days to weeks of commencing a gluten-free diet. Emerging scientific literature contains several reports linking gluten sensitivity states with neuropsychiatric manifestations including autism, schizophrenia, and ataxia. A clinical review of gluten sensitivity is presented alongside a case illustrating the life-changing difference achieved by gluten elimination in a patient with a longstanding history of auditory and visual hallucinations. Physicians in clinical practice should routinely consider sensitivity issues as an etiological determinant of otherwise inexplicable symptoms. Pathophysiologic mechanisms to explain the multisystem symptomatology with gluten sensitivity are considered.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.087
GPT teacher head0.469
Teacher spread0.382 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations41
Published2014
Admission routes1
Has abstractyes

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