Enhanced electrogastrography: A realistic way to salvage a promise that was never kept?
Bibliographic record
Abstract
AIM: To enhance the clinical utility of electrogastrography (EGG), which has been recorded since 1922, but is clinically unutilized. METHODS: An innovative method to salvage the promise of EGG is proposed by introducing a preliminary procedure, while maintaining the electrodes, standardized equipment, and signal processing utilized in the well-established EGG testing of today. The proposed enhanced EGG (EEGG) protocol involves swallowing an ingestible capsule containing miniature electronic oscillator embedded in an expandable, self-disintegratable, biocompatible pseudobesoar residing in the stomach for the duration of the test. The benefits of the proposed approach are outlined, tested and discussed in details. RESULTS: < 0.01) Pearson correlation between gastric motility indices obtained by force transducers implanted directly on the stomach, and the motility indices obtained by EEGG. A particular emphasis was made on preserving standard EGG-related hardware and software in order to facilitate the introduction of the proposed EEGG in environments which already utilize standard EGG testing. The expanded intragastric pseudobezoar containing the miniature electronic oscillator was retained during the tests, and could be disintegrated on demand. CONCLUSION: Enhancing standard EGG by an ingestible, self-expanding and self-disintegrating pseudobesoar containing a miniature electronic oscillator can be an important avenue for clinical applicability of this test.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".