Unbiased Passive Sampling of All Polychlorinated Biphenyls Congeners from Air
Bibliographic record
Abstract
The desire to quantify the presence of a wide range of polychlorinated biphenyls (PCBs) in air is driven both by an interest in the sources and fate of unintentionally produced congeners and in quantifying human inhalation exposure to volatile PCBs. The wide volatility range can introduce bias when sampling the entire suite of PCBs. Here, we present the result of a field calibration experiment that demonstrates that even the most volatile PCBs maintain linear uptake in a passive air sampler using XAD-resin as the sorbent (XAD-PAS). Empirically derived sampling rates ( SR s) for 66 congeners decrease with the number of chlorines and, within a homologue, increase with the number of chlorines in the ortho-position. The large seasonal temperature range at the site of the calibration allowed for an estimation of the temperature dependence of the SR s. The effects of chlorine substitution and temperature can be expressed quantitatively through a regression relating the SR to the sorption constant to XAD from the gas phase. As a result, it is possible to estimate SR s for all congeners at any deployment temperature. The XAD-PAS is well suited for unbiased sampling of gaseous PCBs in a wide variety of settings.
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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 | 0.000 | 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 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".