Non-coeliac gluten sensitivity: are we closer to separating the wheat from the chaff?
Bibliographic record
Abstract
There is growing interest in the role of food as a trigger of functional bowel disorders such as IBS. Indeed, more than 60% of patients with IBS relate the occurrence of bloating and abdominal pain after the ingestion of certain foods.1 Despite intense research in the area, the identification of specific food triggers has remained elusive and this has hampered our understanding of the underlying pathophysiology of these conditions. One clinical entity that embodies the complex relationship between food and gut functional symptoms is non-coeliac gluten sensitivity or non-coeliac wheat sensitivity (NCGS/NCWS) (figure 1). The two names reveal the existing ambiguity regarding the exact component/s in wheat responsible for the worsening or onset of the associated functional symptoms. NCGS/NCWS is thus a clinical descriptor of patients, in whom coeliac disease and wheat allergy have been ruled out, that present with intestinal and/or extra-intestinal symptoms after ingestion of gluten-containing foods.2 One of the dilemmas related to this condition is that this broad definition potentially includes patients with different underlying pathogenesis, leading to confusion in clinical practice and in research studies. Although gluten has been recognised as a trigger of functional symptoms in mice3 and in a subgroup of patients with IBS,4 it is unclear whether non-gluten protein fractions in wheat could also be responsible for symptom generation. While gluten proteins …
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".