A system to evaluate and compare transducers used for lung sound research
Bibliographic record
Abstract
Since lung sounds were first recorded and analyzed in the 1960s, a variety of custom made or adapted transducers have been used for detecting these sounds. There is no standard lung sound transducer nor have those in use been adequately compared. To address this problem, a test platform was constructed that provides a stable and reproducible sound source coupled to a viscoelastic surface that is mechanically and acoustically similar to human skin and subcutaneous tissue as judged from comparisons with similar thicknesses of fresh meat and fat. The device was designed to be equally suitable for air-coupled microphones and for accelerometers. When driven by a broadband noise source, the acoustic amplitude at the surface of the platform was found to be relatively uniform from 100 to 1200 Hz. The system was used to evaluate a variety of lung sound transducers. They were found to vary significantly in frequency response with no device appearing to be adequate as an all-purpose lung sound sensor. It is concluded that lung sound characteristics are likely to be significantly affected by the type of sensor used to acquire the sound. This makes comparisons between differently equipped laboratories difficult.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".