Comparison of flow-sound relationship for different features of tracheal sound
Bibliographic record
Abstract
In recent years, respiratory flow estimation using tracheal sounds has received considerable attention. In this paper, four different features of tracheal sound are investigated and their relationships with flow at different target flow rates are examined during inspiration and expiration phases. The features include average power (AvgPwr), logarithm of the variance (LogVar), logarithm of the range (LogRng) and logarithm of the envelop (LogEnv) of tracheal sound. For each feature a linear model is fitted to the flow and the feature. The results show that LogVar is the best feature to describe flow-sound relationship with a linear model, while the slope of the linear model using AvgPwr shows the largest deviation from a line with changes in target flow rates. Also, the distance from origin of the linear model using any feature changes linearly with variations of target flow.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".