Design, construction, and evaluation of a bioacoustic transducer testing (BATT) system for respiratory sounds
Bibliographic record
Abstract
Many different transducers are employed for recording respiratory sounds including accelerometers and microphones in couplers. However, there is no standard lung sound transducer or any device to compare transducers so that measurements from different laboratories can be determined to be of physiologic origin rather than technical artifacts of the transducers. To address this problem, we designed and constructed a prototype of a device that can be used to compare accelerometers, microphones enclosed in couplers, and stethoscopes. The prototype device consists of a rigid chamber containing a loudspeaker that opens to an antechamber covered by a viscoelastic material with mechanical properties similar to human skin and subcutaneous tissue. When driven by a white noise source, we found the sound output at the surface to be useful to comparatively evaluate sensors between 100 and 1200 Hz where lung sounds have most of their spectral energy. We compared the viscoelastic layer to similar thicknesses of fresh meat and fat and found them to produce similar acoustic spectra. This device allows air-coupled transducers, accelerometers, and stethoscopes used in respiratory sounds measurements to be compared under physical conditions similar to their intended use.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".