Bibliographic record
Abstract
Irritable bowel syndrome (IBS) affects ≈10%–15% of the US population and accounts for one-third to one-half of visits to digestive disease specialists. Given the high prevalence of this disorder, it may be inferred that a significant number of patients with inflammatory bowel disease (IBD) also suffer from overlapping IBS. IBD and IBS often share similar symptoms such as diarrhea and abdominal pain. The high prevalence of IBS in IBD and common symptom features raise an important question: How can IBD be distinguished from IBS? The following discussion aims to address this issue. In the US, two-thirds of patients who seek medical attention for IBS are women. A survey study in North Carolina found that 15% of otherwise healthy college students report symptoms attributable to IBS such as altered bowel habits or nervous diarrhea.1 Another by Thompson and Heaton2 reported a 14% incidence of functional complaints among a healthy English population. Among patients with IBD, the problem is at least equivalent in scope. In a population-based prospective cohort study from Manitoba, 14% of newly diagnosed IBD patients with symptoms for >3 years were considered to also have likely or possible IBS.3
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 | 0.006 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".