Bibliographic record
Abstract
To the Editor: I am very pleased that Professor Walker-Smith has written to further elaborate on the United Kingdom's experience with enteral nutrition in active Crohn's disease. As discussed in my editorial, the difference between United Kingdom and North American management of children with newly diagnosed Crohn's disease is striking. All of us who treat inflammatory bowel disease (IBD), and, indeed, also our patients and their parents should consider enteral nutrition as an option for primary therapy. The attitude of physicians inevitably influences patients in their acceptance or rejection of any treatment or intervention. I agree that prospectively accrued data comparing the frequency of mucosal healing with enteral nutrition versus corticosteroids are important. So, too, is information related to the long-term natural history of Crohn's disease treated from the outset with enteral nutrition versus corticosteroids. If either of these comparisons demonstrates superiority of enteral nutrition, North American recommendations concerning optimal treatment would have to be altered. In the meantime, we should at least endorse enteral nutrition as a treatment without cosmetic adverse effects that “works” frequently in patients with newly diagnosed disease. Given that there is no evidence that amino-acid–based formulae are required, we should encourage the use of more palatable formulae to facilitate oral consumption. Anne M. Griffiths
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".