Manometry-Based Cough Identification Algorithm
Why this work is in the frame
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Bibliographic record
Abstract
Gastroesophageal reflux disease (GERD) is a common cause of chronic cough. For the diagnosis and\ntreatment of GERD, it is desirable to quantify the temporal correlation between cough and reflux events. Cough\nepisodes can be identified on esophageal manometric recordings as short-duration, rapid pressure rises. The\npresent study aims at facilitating the detection of coughs by proposing an algorithm for the classification of cough\nevents using manometric recordings. The algorithm detects cough episodes based on digital filtering, slope and\namplitude analysis, and duration of the event. The algorithm has been tested on in vivo data acquired using a\nsingle-channel intra-esophageal manometric probe that comprises a miniature white-light interferometric fiber\noptic pressure sensor. Experimental results demonstrate the feasibility of using the proposed algorithm for\nidentifying cough episodes based on real-time recordings using a single channel pressure catheter. The\npresented work can be integrated with commercial reflux pH/impedance probes to facilitate simultaneous 24-hour\nambulatory monitoring of cough and reflux events, with the ultimate goal of quantifying the temporal correlation\nbetween the two types of events.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it