Bibliographic record
Abstract
Abstract This statement defines probiotics and reviews the most recent literature on their use in paediatrics. Many studies have examined the potential benefit of probiotics, but significant variation in the strains and doses of probiotics used, the patient populations studied, and in study design, have led to heterogeneous results. Present evidence suggests that probiotics can decrease mortality and lower incidence of necrotizing enterocolitis in preterm and low birth weight neonates. Probiotics may also be beneficial in reducing feeding intolerance. In infants, probiotics may be considered to reduce symptoms of colic. In older children, probiotics can be considered to prevent antibiotic-associated diarrhea and Clostridium difficile-associated diarrhea. Probiotic supplements used in conjunction with standard therapy can help with Helicobacter pylori eradication and decrease the side effects of treatment. Lactobacillus species can be considered to treat irritable bowel syndrome. Probiotics can also be considered to help prevent atopic dermatitis and eczema. To optimize paediatric policy and practice, large, quality studies are needed to determine what types and combinations of probiotics are most efficacious.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".