Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
PURPOSE OF REVIEW: Enteral nutrition is now the preferred route of nutritional support in malnourished and ICU patients. Studies providing evidence of its efficacy, techniques of administration, and outcome are appearing daily in the literature. This review presents the most important publications in this area and critically reviews them. In this way, the reader can rapidly access important publications from all those that are being published each year. RECENT FINDINGS: A diverse group of studies is covered in this review. The subjects of these studies include the role of enteral and parenteral nutrition in the perioperative patient; reinfusion of succus to promote increased absorption in patients with a fistula or short bowel; enteral nutrition in patients with head injury, in liver disease, and in pancreatitis; bone marrow transplantation; and delivery of enteral nutrition. SUMMARY: Enteral nutrition is an established modality of nutritional support that has received wide acceptance. However, it is not clear in which conditions it improves patient outcome and how to optimize its delivery. In this review, articles addressing the outcome of patients and methods to optimize delivery of enteral nutrition are reviewed. Unfortunately, with few exceptions, most studies are based on few patients or do not have a placebo arm. The usual comparison is with total parenteral nutrition, and in such comparisons, the studies fail to make the two groups comparable in terms of energy intake and the occurrence of a major risk factor for sepsis, namely, hyperglycemia.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.011 |
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".