A Meta-analysis of Risk Factors for Irritable Bowel Syndrome in China
Bibliographic record
Abstract
In order to systematically evaluate the risk factors for irritable bowel syndrome, We searched CNKI, Wanfang, Weipu and PubMed databases for risk factors for irritable bowel syndrome in China, Newcastle-Ottawa Scale (NOS) used the most comprehensive data collection based on relevant case-control trials, combined with inclusion and exclusion criteria to evaluate the quality of the extracted literature, included the literature with a score of ≥7, and finally meta-analyzed using RevMan 5.4. In the end, 15 articles met the inclusion criteria, with a cumulative number of 5171 cases and 3088 controls, respectively. It was concluded that history of alcoholism, spicy food, seafood, irregular diet, gastrointestinal infection, drug history, anxiety (long-term tension), sleep disorder (insomnia), personality sensitivity (introversion), family history of IBS, smoking, psychiatric (psycho-depressive factors), and family and marital events were independent risk factors for IBS, and controlling the above factors could effectively reduce the risk of IBS patients.
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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.037 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".