Variability of hearing protection devices attenuation as a function of source location
Bibliographic record
Abstract
It is of common knowledge, and well documented, that laboratory-measured noise attenuation values of most hearing protection devices (HPD) exceed significantly the attenuation values obtained in real-world workplace environments. Various reasons may explain such discrepancies (lack of training, wearing time, lack of comfort, bad fitting, noise environments, etc.) but very few of them have been studied in details due to the complexity of the problem. This study focuses on the variability of the attenuation of HPDs as a function of the location of the noise source. Laboratory measurements were performed where subjects, wearing a HPD and facing a loudspeaker, were asked to rotate slowly on a rotating chair to simulate different angular positions of the head relative to the source. The protected and unprotected sound pressure signals for both ears were recorded as time signals using miniature microphones placed respectively inside and outside the HPD (F-MIRE technique). The microphones signals were processed to obtain attenuation values for the different angular positions. Results for different type of HPD (ear-muffs and ear-plugs) are presented and discussed.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".