Bibliographic record
Abstract
Probiotics are living microorganisms that can affect the host in a beneficial manner. Prebiotics are nondigestible food ingredients that stimulate the growth and activity of probiotic bacteria already established in the colon. Efficacy of probiotic compounds has been shown in a wide range of gastrointestinal diseases. Lactobacillus GG alone, or the combination of Bifidobacterium bifidum and Streptococcus thermophilus, is effective in the treatment of Clostridium difficile, as well as in preventing the frequency and severity of infectious acute diarrhea in children. Prevention of antibiotic-induced diarrhea with the concomitant administration of either Lactobacillus GG or Saccharomyces boulardii has been demonstrated. The most successful studies involve the use of Lactobacillus GG at a dose of 1 x 1010 viable organisms per day and the yeast boulardii at a dose of 1 g/day. A probiotic preparation (VSL#3 - 6 g/day) that uses a combination of three species of Bifidobacterium, four strains of Lactobacillus and one strain of Streptocccus has shown promise in maintaining remission in ulcerative colitis and pouchitis, as well as in preventing the postoperative recurrence of Crohn's disease. The mechanism of action of probiotics may include receptor competition, effects on mucin secretion or probiotic immunomodulation of gut-associated lymphoid tissue. Oral administration of probiotic compounds has been demonstrated to be well tolerated and safe. However, while probiotics have the potential to improve human health and to prevent and treat some diseases, major improvements are needed in labelling and quality assurance procedures for probiotic compounds. In addition, well planned and controlled clinical studies are necessary to delineate fully the potential for probiotic compounds.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".