Review: probiotics reduced diarrhoea at 3 days in children and adults with proven or presumed infectious diarrhoea
Bibliographic record
Abstract
Allen SJ, Okoko B, Martinez E, et al . Probiotics for treating infectious diarrhoea. Cochrane Database Syst Rev 2004;(2):CD003048. Q Are probiotics effective for proven or presumed infectious diarrhoea in children and adults? ### ![Graphic][1] Data sources: Cochrane Infectious Diseases Group trials register (December 2002), Cochrane Controlled Trials Register (Issue 4, 2002), Medline (1966–2002), and EMBASE/Excerpta Medica (1988–2002); existing reviews; reference lists of retrieved trials; experts and relevant organisations; and 5 manufacturers of probiotics. ### ![Graphic][2] Study selection and assessment: published and unpublished randomised controlled trials (RCTs) in any language that compared specific probiotics with placebo or no probiotic in adults and children with acute diarrhoea (<14 d) that was proven or presumed to be caused by an infectious agent. 2 independent reviewers assessed … [1]: /embed/inline-graphic-1.gif [2]: /embed/inline-graphic-2.gif
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 | 0.004 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".