Potential Uses of Probiotics in Clinical Practice
Bibliographic record
Abstract
Probiotics are defined as live microorganisms that, when administered in adequate amounts, confer a health benefit on the host. There is now mounting evidence that selected probiotic strains can provide health benefits to their human hosts. Numerous clinical trials show that certain strains can improve the outcome of intestinal infections by reducing the duration of diarrhea. Further investigations have shown benefits in reducing the recurrence of urogenital infections in women, while promising studies in cancer and allergies require research into the mechanisms of activity for particular strains and better-designed trials. At present, only a small percentage of physicians either know of probiotics or understand their potential applicability to patient care. Thus, probiotics are not yet part of the clinical arsenal for prevention and treatment of disease or maintenance of health. The establishment of accepted standards and guidelines, proposed by the Food and Agriculture Organization of the United Nations and the World Health Organization, represents a key step in ensuring that reliable products with suitable, informative health claims become available. Based upon the evidence to date, future advances with single- and multiple-strain therapies are on the horizon for the management of a number of debilitating and even fatal conditions.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".