Effect of a level-dependent hearing protector on detection thresholds, perceived urgency, and localization performance of reverse alarms
Bibliographic record
Abstract
Previous studies have shown that perception of warning signals in noisy workplaces can be compromised when wearing conventional hearing protectors. Level-dependent hearing protectors have been developed to increase environmental awareness and, by extension, to improve worker safety. A set of studies was conducted to assess the potential benefits of a level-dependent hearing protector operating in its passive and active modes, in quiet and in noise, for a range of listeners with normal hearing listening to reverse alarms. As expected, the detection of reverse alarms in quiet was improved in the active mode compared to the passive mode, but no significant benefit was found in noise. The active mode of the device only marginally helped to restore the sense of urgency conveyed by back-up alarms in noise, which was largely affected by passive attenuation.The localization of reverse alarms was slightly worse when wearing the device compared to unprotected listening, and was not improved in the active mode compared to the passive mode. In summary, when choosing a hearing protector to ensure adequate perception of reverse alarms, for example, different psychoacoustic tasks must be considered, also keeping in mind that level-dependent hearing protection does not necessarily restore performance to unprotected targets.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".