Temporal Variations of Cyclic\nand Linear Volatile\nMethylsiloxanes in the Atmosphere Using Passive Samplers and High-Volume\nAir Samplers
Bibliographic record
Abstract
Cyclic\nand linear volatile methylsiloxanes (cVMSs and lVMSs, respectively)\nwere measured in ambient air over a period of over one year in Toronto,\nCanada. Air samples were collected using passive air samplers (PAS)\nconsisting of sorbent-impregnated polyurethane foam (SIP) disks in\nparallel with high volume active air samplers (HV-AAS). The average\ndifference between the SIP-PAS derived concentrations in air for the\nindividual VMSs and those measured using HV-AAS was within a factor\nof 2. The air concentrations (HV-AAS) ranged 22–351 ng m<sup>–3</sup> and 1.3–15 ng m<sup>–3</sup> for ΣcVMSs\n(D<sub>3</sub>, D<sub>4</sub>, D<sub>5</sub>, D<sub>6</sub>) and ΣlVMSs\n(L<sub>3</sub>, L<sub>4</sub>, L<sub>5</sub>), respectively, with\ndecamethylcyclopentasiloxane (D<sub>5</sub>) as the dominant compound\n(∼75% of the ΣVMSs). Air masses arriving from north to\nnorthwest (i.e., less populated areas) were significantly less contaminated\nwith VMSs compared to air arriving from the south that are impacted\nby major urban and industrial areas in Canada and the U.S. (<i>p</i> < 0.05). In addition, air concentrations of ΣcVMSs\nwere lower during major snowfall events (on average, 73 ng m<sup>–3</sup>) in comparison to the other sampling periods (121 ng m<sup>–3</sup>). Ambient temperature had a small influence on the seasonal trend\nof VMS concentrations in air, except for dodecamethylcyclohexasiloxane\n(D<sub>6</sub>), which was positively correlated with the ambient\ntemperature (<i>p</i> < 0.001).
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How this classification was reachedexpand
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) | 0.006 | 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 teacher head, 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".