Effects of ear canal occlusion on hearing sensitivity: A loudness experiment
Bibliographic record
Abstract
Over the last century, hearing research has repeatedly reported differences in loudness perception when different types of transducers are being used. One of the effects of using different transducers is that listening may be performed via an open ear (loudspeaker), a cushioned ear (headphones), or an occluded ear (hearing aid receivers, insert earphones). The question of whether varying the acoustic load applied to the ear canal might impact hearing sensitivity has therefore become essential given the need to establish realistic noise damage risk criteria in an attempt to prevent noise-induced hearing loss for any given listening condition. Although such loudness discrepancies in the cushioned ear have been recently proven to be caused by loudness measurement artifacts, currently available data do not exclude a possible impact of ear canal occlusion on loudness perception. This paper presents the results of a loudness balance test carried out on 18 normal-hearing listeners. Using an earplug to occlude the canal, in-ear sound pressure levels were compared between the occluded ear and the cushioned ear at equal loudness. The results show agreement within 1 dB between the two listening conditions, and support the conclusion that loudness does not depend on the type of acoustic load applied to the ear canal.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".