Bibliographic record
Abstract
Esophageal disorders are common in the general population and can be associated with significant morbidity. Several new diagnostic techniques for esophageal disorders have become available in recent years. These include capsule pH-metry, high-resolution manometry, impedance combined with either pH-metry or manometry, and high-frequency ultrasound. Capsule pH-metry is useful in children and in patients who cannot tolerate the conventional pH-metry catheter. It has the advantage of not interfering with a patient's usual meals and activities during the 24 h study. High-resolution manometry is easier to perform and interpret than conventional manometry. This has led to improved diagnosis of various esophageal motility disorders. Impedance measures the movement of liquid and gas in the esophagus. When combined with pH-metry, impedance can confirm that retrograde bolus movement (ie, reflux) is occurring while simultaneously measuring changes in pH levels. It has also highlighted the importance of weakly acidic reflux in patients who do not respond to proton pump inhibitors. Weakly acidic reflux cannot be diagnosed with pH-metry alone. Impedance combined with manometry can determine whether a manometric abnormality leads to abnormal bolus clearance. In the past, this was performed with fluoroscopy, yet impedance is equally effective and does not carry the risk of increased radiation exposure. High-frequency ultrasound is currently a research tool to image the esophageal wall, particularly the two muscle layers, in real time during swallows and at rest. It has broadened our understanding of the pathophysiology of esophageal motility disorders.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".