Bibliographic record
Abstract
Cystic fibrosis (CF) is an autosomal recessive disease. It affects multiple body organs. The lungs and pancreas are the most affected which results in progressive lung damage and pancreatic insufficiency. Due to the disease process, CF patients require significantly higher caloric intake than recommended for other individuals. The nutritional goal for CF patients is to achieve normal growth and development and, once genetic potential is reached, to maintain good nutritional status throughout life. Evidence has shown that lung function is closely associated with nutritional status in CF and that nutritional status is an independent predictor of survival. Most CF patients are on a high calorie diet to help achieve normal growth and development and maintain good lung function. Inadequate caloric intake in CF can lead to malnutrition. Malnutrition in CF requires careful, multidisciplinary history taking, physical exam, and overall patient/family assessment. Only by determining the actual cause of the malnutrition can appropriate and safe therapies be used to treat it. Appetite stimulants, although efficacious in treating malnutrition in CF, should only be prescribed if decreased food intake secondary to inadequate appetite is the principal cause of the malnutrition and all other contributing factors have been assessed, ruled-out or treated. In this review, we attempted to summarize the use of several appetite stimulants used in CF and other diseases to improve appetite and maximize caloric intake.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".