Electron Microscopy Study of Refractory Ceramic Fibers
Bibliographic record
Abstract
In epidemiological studies designed to identify potential health risks of exposures to synthetic vitreous fibers, the characterization of airborne fiber dimensions may be essential for assessing mechanisms of fiber toxicity. Toward this end, air sampling was conducted as part of an industry-wide study of workers potentially exposed to airborne fibrous dusts during the manufacture of refractory ceramic fibers (RCF) and RCF products. Analyses of a subset of samples obtained on the sample filter as well as on the conductive sampling cowl were performed using both scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to characterize dimensions of airborne fibers. Comparison was made of bivariate fiber size distributions (length and diameter) from air samples analyzed by SEM and by TEM techniques. Results of the analyses indicate that RCF size distributions include fibers small enough in diameter (< 0.25 microm) to be unresolved by SEM. However, longer fibers (> 60 microm) may go undetected by TEM, as evidenced by the proportion of fibers in this category for TEM and SEM analyses (1% and 5%, respectively). Limitations of the microscopic techniques and differences in fiber-sizing rules for each method are believed to have contributed to the variation among fiber-sizing results. It was concluded from these data that further attempts to characterize RCF exposure in manufacturing and related operations should include analysis by TEM and SEM, since the smallest diameter fibers are not resolved with SEM and the fibers of longer length are not sized by TEM.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".