Particle Size Distribution in Aluminum Manufacturing Facilities
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Bibliographic record
Abstract
As part of exposure assessment for an ongoing epidemiologic study of heart disease and fine particle exposures in aluminum industry, area particle samples were collected in production facilities to assess instrument reliability and particle size distribution at different process areas. Personal modular impactors (PMI) and Minimicro-orifice uniform deposition impactors (MiniMOUDI) were used. The coefficient of variation (CV) of co-located samples was used to evaluate the reproducibility of the samplers. PM2.5 measured by PMI was compared to PM2.5 calculated from MiniMOUDI data. Mass median aerodynamic diameter (MMAD) and concentrations of sub-micrometer (PM1.0) and quasi-ultrafine (PM0.56) particles were evaluated to characterize particle size distribution. Most of CVs were less than 30%. The slope of the linear regression of PMI_PM2.5 versus MiniMOUDI_PM2.5 was 1.03 mg/m3 per mg/m3 (± 0.05), with correlation coefficient of 0.97 (± 0.01). Particle size distribution varied substantively in smelters, whereas it was less variable in fabrication units with significantly smaller MMADs (arithmetic mean of MMADs: 2.59 µm in smelters vs. 1.31 µm in fabrication units, p = 0.001). Although the total particle concentration was more than two times higher in the smelters than in the fabrication units, the fraction of PM10 which was PM1.0 or PM0.56 was significantly lower in the smelters than in the fabrication units (p < 0.001). Consequently, the concentrations of sub-micrometer and quasi-ultrafine particles were similar in these two types of facilities. It would appear, studies evaluating ultrafine particle exposure in aluminum industry should focus on not only the smelters, but also the fabrication facilities.
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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 it