Estimation of noise exposure level for subjects wearing hearing protector devices
Bibliographic record
Abstract
Industrial workers are exposed to noise levels that could damage their hearing. The FieldMIRE (FMIRE) method has been developed to quantify earplug and earmuff attenuations with two microphones located under and outside of the HPD. This technique has been designed to be used in the field, but doesn't give a direct access to the noise exposure level, that is, the noise level at the head location without the subject. In this article we present a combination of the FMIRE method with a proposed technique to estimate the sound pressure level without subject, in order to quantify both the ambient and protected noise exposure levels and deduce the effects on worker hearing. Several experiments have been conducted on four subjects with three types of earplugs and with five types of earmuffs. Firstly, the best location for the microphone outside of the HPD has been determined. Secondly, correction factors that need to be applied on the outside microphone measurement to estimate the sound pressure level without subject have been quantified. Finally the proposed technique has been validated with measurements taken in a simulated workplace.
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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 | 0.001 |
| 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".