Measurement of ambient fiber and fibrous glass concentrations near three fiberglass wool manufacturing facilities in the United States
Bibliographic record
Abstract
A limited number of published studies have evaluated concentrations of airborne fibers in outdoor air, with even fewer assessing typical air concentrations in the ambient air near fiberglass wool manufacturing facilities. Building upon the assessment by Switala et al. (Citation1994), area samples for airborne fiber concentrations (diameters of less than 3 µm, lengths greater than 5 µm, and aspect ratios equal to or greater than 5 to 1) were collected at fixed locations along the fence lines of three fiberglass wool manufacturing facilities in the United States. Samples were analyzed by the National Institute for Occupational Safety and Health (NIOSH) Method 7400, via phase contrast microscopy (PCM) using “B” counting rules. A total of 134 samples were collected across the three plants. Overall, 73% of the samples collected were below the limit of quantification (LOQ). Using the Kaplan–Meier (KM) method for estimation of values below the LOQ, the geometric mean fiber concentration for all plants combined was 0.0028 fibers per cubic centimeter (f/cc), with the 95th percentile upper confidence level at 0.0049 f/cc. Of those samples with detectable concentrations of airborne fibers (n = 36), when further analyzed using energy dispersive X-ray (EDX) analysis, only one sample had a detectable glass fiber concentration at 0.0045 f/cc, which was noted as the detection limit for the method. This glass fiber concentration is within the range anticipated for ambient fibrous glass near production facilities, suggesting consistency with measurements made by Switala et al. (Citation1994), despite changes in production methods (i.e., use of different binders) since 1994 and the use of updated methods for treatment of values below the LOQ in the current assessment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".