Pilot study on individual dose-response relationship evaluated through otoacoustic emission measurements in controlled noise exposure: influence of circadian rhythm
Bibliographic record
Abstract
Over 22 million of North American workers are exposed daily to noise doses that may induce hearing loss. Unfortunately, current practices to prevent occupational noise-induced hearing loss (NIHL) based on group average of exposure/damage relationships do not account for the individual’s susceptibility. Consequently, NIHL remains one of the biggest cause of invalidity and indemnity in North America. To improve hearing conservation in the workplace, a procedure to continuously measure hearing fatigue using otoacoustic emissions (OAE) has been developed using a portable and robust OAE system designed for noisy field use. A pilot study has been conducted on human subjects in laboratory, playing back pre-recorded noise samples at realistic levels while recording the accumulated individual noise dose. To monitor the temporary effects (response) on the individuals’ inner-ear during the exposure, OAEs were measured periodically on subjects using either the designed OAE system or a reference OAE system. Audiometric thresholds, stapedius and medial olivocochlear reflex were also measured pre and post-exposure to monitor other potential effects on hearing. The potential effects of circadian rhythm on pre and post-exposure measurements are briefly studied here.
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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 | 0.002 |
| 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) | 0.001 | 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".