Temporal Variations of Cyclic and Linear Volatile Methylsiloxanes in the Atmosphere Using Passive Samplers and High-Volume Air Samplers
Bibliographic record
Abstract
Cyclic and linear volatile methylsiloxanes (cVMSs and lVMSs, respectively) were measured in ambient air over a period of over one year in Toronto, Canada. Air samples were collected using passive air samplers (PAS) consisting of sorbent-impregnated polyurethane foam (SIP) disks in parallel with high volume active air samplers (HV-AAS). The average difference between the SIP-PAS derived concentrations in air for the individual VMSs and those measured using HV-AAS was within a factor of 2. The air concentrations (HV-AAS) ranged 22-351 ng m(-3) and 1.3-15 ng m(-3) for ΣcVMSs (D3, D4, D5, D6) and ΣlVMSs (L3, L4, L5), respectively, with decamethylcyclopentasiloxane (D5) as the dominant compound (∼75% of the ΣVMSs). Air masses arriving from north to northwest (i.e., less populated areas) were significantly less contaminated with VMSs compared to air arriving from the south that are impacted by major urban and industrial areas in Canada and the U.S. (p < 0.05). In addition, air concentrations of ΣcVMSs were lower during major snowfall events (on average, 73 ng m(-3)) in comparison to the other sampling periods (121 ng m(-3)). Ambient temperature had a small influence on the seasonal trend of VMS concentrations in air, except for dodecamethylcyclohexasiloxane (D6), which was positively correlated with the ambient temperature (p < 0.001).
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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 | 0.001 |
| 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".