The objective measurement of individual earplug field performance
Bibliographic record
Abstract
This paper presents a field-microphone-in-real-ear (MIRE) method for the objective measurement of individual earplug field attenuation. This development was made possible by using a recently designed instrumented expandable custom earplug. From the measurement of the noise reduction (NR) through the earplug, this method predicts the attenuation that would be experienced by the wearer and that would be measured using the real-ear attenuation at threshold (REAT) method. Formulations presented include establishing the relationship between NR, insertion loss, and REAT, as well as defining the laboratory and field calibration procedures required to determine the correction factors to be applied to the measured NR. This method was validated experimentally by comparing the predicted field-MIRE attenuation values to the REAT values measured on a group of test-subjects. This method offers fast and accurate measurement of earplug field performance on an individual basis and could lead to further developments for effective hearing protection practices as well as for hearing protection device rating and labeling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".