Bibliographic record
Abstract
Inflammatory bowel disease (IBD) is one of the most active and exciting fields in medicine and is an intense focus of development and innovation in research and patient care. We now have at least 7 different biologic agents to treat our moderate to severely active patients, multiple blood and stool tests to measure response to treatment and an ever expanding array of potential genes, cytokines, and fecal microbiota to test as potential causes and treatment targets. Yet, despite impressive advances in discovering the etiology of IBD and the development of effective targeted medications to treat the disease, there is still one area of the field where our knowledge is still in its infancy; that of the diagnosis and treatment of sexual dysfunction. In 2 meticulously researched and written articles, Ghazi et al1 and Jedel et al2 detail all of the relevant studies published on the topic of sexual function in women and men with IBD. The Ghazi review is comprehensive and examines all of the literature regarding the causes of sexual dysfunction in both medical and surgical patients. Jedel et al do a complete review of the sexual function and body image literature and look at the impact of both on quality of life. Taken together, both articles are excellent evidence-based reviews, and all one needs to learn past and current research in the field.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".