Méthode de mesures terrain de l'atténuation F-MIRE de protecteurs auditifs durant un quart de travail
Bibliographic record
Abstract
Nowadays, hearing protection devices (HPD) are widely used to protect workers against industrial noise, however, a question worth examining is: "Is the worker truly provided with, at all times, protection that is as effective as what the manufacturer is advertising, based on standardized testing?" It is a commonly known and well documented fact that compared to values obtained from various existing field studies laboratory-measured noise attenuation values overestimate the actual protection being provided to workers. Too few studies are available on this topic, and the issues concerning HPD field measurement are still far from being resolved. Even if several field measurement methods have been developed, none has succeeded in being recognized as a standard. Therefore, the need for a new field measurement method, one which could become a recognized reference, is as relevant as ever. This paper presents a new field measurement method developed to quantify the in-field attenuation HPDs provide to workers. This method is designed to take ongoing measurements during a complete work shift (8 hours) and enable the measurement of the actual attenuation being provided to the worker in his work environment, for different types and levels of industrial noise. The measurement method is based on the F-MIRE protocol using a miniature double microphone that allows for simultaneous measurement of the sound pressure inside the protector and the sound field surrounding the worker. The time signals recorded are then analyzed in order to determine the overall protection, and also, to assess performance over time. Results from preliminary measurements obtained from factory workers are presented in order to fully illustrate the range of analysis possibilities of this new field measurement method.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".