Use of Benzo[a]pyrene Relative Abundance Ratios to Assess Exposure to Polycyclic Aromatic Hydrocarbons in the Ambient Atmosphere in the Vicinity of a Söderberg Aluminum Smelter
Bibliographic record
Abstract
The purpose of this study was to investigate the use of benzo[a]pyrene (B[a]P) relative abundance ratios (RARs) to assess exposure to polycyclic aromatic hydrocarbons (PAHs) in the urban atmospheric air in the vicinity of a horizontal stud Söderberg aluminum reduction facility. The B[a]P RARs refer to the concentration of individual PAHs measured in a given sample divided by the concentration of B[a]P found in the same sample. This study compared the B[a]P RARs calculated for the facility stack and three sites near the Söderberg aluminum smelter for three different sampling periods. Interperiod differences were significant for many of the PAHs, and the differences between the stations proved insignificant at p < 0.05. The differences between each individual station and the facility stack were significant for all PAHs. B[a]P RARs increased in value at the stations compared with the stack, indicating that B[a]P may be degraded or removed from the atmosphere at a rate greater than that of the majority of the measured PAHs. It is concluded that B[a]P and B[a]P RARs may be poor markers of exposure to PAHs in the vicinity of this Söderberg aluminum refinery for the entire mixture of PAHs present in the ambient atmosphere.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".