Assessment of sorbent impregnated PUF disks (SIPs) for long-term sampling of legacy POPs
Bibliographic record
Abstract
Two field studies were conducted for one year using sorbent-impregnated polyurethane foam (SIP) disks for PCB and PBDE air sampling. SIP disks were introduced by Shoeib et al. (2008) as an alternative passive air sampling medium to the polyurethane foam (PUF) disk and have the advantage of a higher holding capacity for organic chemicals. The first study on SIP disks confirmed their application for measuring volatile perfluorinated compounds (PFCs) and their ability to maintain time-integrated (linear) air sampling. In this study, the suitability of the SIP disks for long-term sampling of polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and hexachlorobenzene (HCB) was assessed. SIP disks were deployed at a rural site in the UK and harvested after periods ranging from 35-350 days. Atmospheric POP concentrations were monitored with a high-volume air sampler during the deployment period. Linear uptake was observed for all monitored PCBs and PBDEs over the full exposure time. Air-sampler equilibrium was observed for HCB after 6 months. In a second field study, SIP disks were deployed for one year at 10 sites on a latitudinal transect in the UK and Norway, at which air sampling has been undertaken previously with different passive air sampling media since 1994. The estimated concentrations and spatial distributions derived from the SIP disks were largely in agreement with previously reported data.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".