Catheter-based acoustic interrogation device for real-time monitoring of the dynamics of the lower esophageal sphincter:<i>in vitro</i>and pilot canine studies
Bibliographic record
Abstract
This paper presents a novel minimally-invasive catheter-based acoustic interrogation device for real-time monitoring the dynamics of the lower esophageal sphincter (LES). Dysfunction of the LES could result gastrointestinal (GI) diseases, such as gastroesophageal reflux disease (GERD). A micro-oscillator actively emitting sound wave at 16 kHz is located at one side of the LES, and a miniature microphone is located at the other side of the LES to capture the sound generated from the oscillator. Thus, the dynamics of the opening and closing of the LES can be monitored. The device was tested in vitro by utilizing a custom-designed LES simulator, as well as in vivo in a pilot canine model. In the in vitro test, the sound was captured by the microphone and its strength was correlated with the level of LES opening and closing which was controlled by the simulator. The measurements showed statistically significant (p < 0.05) Pearson correlation coefficients (0.905 on the average in quiet environment and 0.736 on the average in noisy environment, DOF = 9). In the in vivo test, the LES was forced open and closed by a transoral endoscope, which was monitored in real-time by a transpyloric endoscope inserted from the duodenum and positioned into the distal stomach. Frame-by-frame video analysis validated the interrelation between the sound strength and the LES opening and closing. The LES dynamics monitored by the proposed device has the potential to become a valuable minimally-invasive technique for understanding LES dysfunction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".