Global Distribution of Linear and Cyclic Volatile Methyl Siloxanes in Air
Bibliographic record
Abstract
The global distribution of linear and cyclic volatile methyl silxoanes (VMS) was investigated at 20 sites worldwide, including 5 locations in the Arctic, using sorbent-impregnated polyurethane foam (SIP) disk passive air samplers. Cyclic VMS are currently being considered for regulation because they are high production volume chemicals that are potentially persistent, bioaccumulative, and toxic. Linear and cyclic VMS (including L3, L4, L5, D3, D4, D5, and D6) were analyzed for in air at all urban, background, and Arctic sites. Concentrations of D3 and D4 are significantly correlated, as are D5 and D6, which suggests different sources for these two pairs of compounds. Elevated concentrations of D3 and D4 on the West coast of North America and at high elevation sites suggest these sites are influenced by trans-Pacific transport, while D5 and D6 have elevated concentrations in urban areas, which is most likely due to personal care product use. Measured concentrations of D5 were compared to modeled concentrations generated using both the Danish Eulerian Hemispheric Model (DEHM) and the Berkeley-Trent Global Contaminant Fate Model (BETR Global). The correlation coefficients (r) between the measured and modeled results were 0.73 and 0.58 for the DEHM and BETR models, respectively. Agreement between measurements and models indicate that the sources, transport pathways, and sinks of D5 in the global atmosphere are fairly well understood.
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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 | 0.000 | 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".