Bibliographic record
Abstract
Respirator fit testing is necessary before entering hazardous working environments to ensure that the respirator, when worn, satisfies a minimum fit and that the wearer knows when the respirator fits properly. In the many countries that do not have fit testing or total inward leakage regulations (including Korea), however, many workers wearing respirators may be potentially exposed to hazardous environments. It is necessary to suggest a useful tool to provide an alternative for fit testing in these countries. This study was conducted to evaluate fitting performance for quarter-mask respirators, and fit factors in facial size categories based on face lengths and lip lengths of the wearers. A total of 778 subjects (408 males, 370 females) were fit tested for three quarter masks: Sejin Co. SK-6 (Ulsan, Korea), Yongsung Co. YS-2010 S (Seoul, Korea), and 3 M Co. Series 7500 Medium (MN, USA) masks with a PortaCount 8020 (TSI Co., USA). A facial dimension survey of the subjects was conducted to develop facial size categories, on the basis of face length and lip length. Geometric mean fit factors (GMFFs) of Series 7500 Medium were found to be the highest of the three respirators. All of the respirators were more suitable for males than females in fitting performance. The Series 7500 Medium fitted a large number of the males tested, since the GMFFs for males were above 100 for every box of facial size categories, and high pass proportion rates were shown at an individual fit factor level of 100. The YS-2010 S provides an adequate fit for males in a limited range of facial dimensions. The Series 7500 Medium is more limited in providing adequate fit for females at specific facial dimensions than for males. For adequate fitting performance, the SK-6 is not preferentially recommended for Korean male and female workers due to low GMFFs and pass proportions. The result of this study indicates that after more accurate studies are performed, facial size categories, on the basis of facial dimensions, could be a useful tool to assist in the selection of adequately fitting respirators for workers in the countries having no fit testing requirements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".