A finite element model to study the earplug contribution to the objective occlusion effect
Bibliographic record
Abstract
The use of earplugs is commonly associated with an amplification of low frequency physiological noises in the earcanal referred to as the occlusion effect. In the literature, the type of earplug has been shown to significantly influence the occlusion effect in particular when inserted deeply enough. However, few studies have investigated the physical mechanisms that rule the earplug contribution. Their understanding is necessary to ultimately act on the earplug to reduce the occlusion effect. Classical lumped element models usually simplify the earplug as an impedance connected to the earcanal cavity. Intricate couplings of the earplug with the earcanal wall and the earcanal cavity are thus neglected. Finite element models can account for these couplings and thus make it possible to study the earplug contribution. In this work, the physical mechanisms that explain the earplug contribution to the objective occlusion effect are investigated. For this purpose, a 2-D axi-symmetric finite element model of an outer ear is used. Two types of earplug (foam and silicone) as well as two insertion depths (medium and deep) are considered. The earplug influence is interpreted in terms of volume velocity imposed to the earcanal cavity and related to its mechanical properties and its insertion depth.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".