Measurements in the Open and Closed Ear Canal: Comparison Between Different Artificial Head Concepts
Bibliographic record
Abstract
A specific artificial head dedicated to the study of hearing protection was designed by the IRSST and the ETS (Ref). This head was fabricated from medical images (MRI) of a human participant and allows for the transmission of sound by bone and cartilage conduction to be taken into account in order to study the occlusion effect of earplugs. The bony structure of the skull and the cartilage of the ear are covered with a soft material of varying thickness in order to reproduce all the human soft tissues (skin, muscle and fat). The objective of this study is to evaluate the ability of this artificial head at capturing the structure and airborne transmission when the ears are open or occluded by a premolded earplug. This is achieved by carrying out several acoustic measurements using a microphone probe inserted into the open and occluded ear canal and comparing them with those made using standard artificial heads and 3 volunteer subjects. The standard artificial head (manufactured by the ISL) is fitted with two external ears, different in terms of shape and material hardness. With an electrodynamic transducer, we measure the occlusion effect and the propagation velocity between the transducer and the probe. We then evaluate the open ear transfer function and an earplug insertion loss in a diffuse field. Results show, in particular, that the specific artificial head gives a realistic occlusion effect, but the measured earplug attenuation is close to zero at low frequencies. The insertion loss of the standard head’s softer ear better corresponds to the measurements on the volunteers. © 2023, Canadian Acoustical Association. All rights reserved.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".