Bibliographic record
Abstract
PURPOSE OF REVIEW: Gastroesophageal reflux disease (GERD) is a common chronic disorder often successfully treated, although there are several evolving issues in management. We reviewed the issues related to unmet needs over the past 12 months. RECENT FINDINGS: A substantial number of patients fail to respond adequately to once or even twice daily proton pump inhibitor (PPI). There is no standard definition of PPI failure in GERD; a universally accepted definition for treatment success is also not available. Differentiation between erosive esophagitis and nonerosive reflux disease can be made but requires endoscopy; but studies still confuse functional heartburn and nonerosive reflux disease, which impacts management. Acid reflux plays an important role in GERD pathogenesis and the precise role of acid requires more studies of differences between erosive esophagitis and nonerosive reflux disease symptom generation and the implication of nocturnal acidification. Several possible mechanisms may explain GERD refractory to PPIs. SUMMARY: Management of PPI nonresponders remains a challenge. Objective and precise evaluation of symptoms and treatment response requires study in high-quality trials. New therapeutic approaches are under investigation to answer unmet needs and improve erosive esophagitis healing rates and symptom control.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".