Synthetic Musk Fragrances in Lake Erie and Lake Ontario Sediment Cores
Bibliographic record
Abstract
Two sediment cores collected from Lake Ontario and Lake Erie were sectioned, dated, and analyzed for five polycyclic musk fragrances and two nitro musk fragrances. The polycyclic musk fragrances were HHCB (Galaxolide), AHTN (Tonalide), ATII (Traseolide), ADBI (Celestolide), and AHMI (Phantolide). The nitro musk fragrances were musk ketone and musk xylene. Chemical analysis was performed by gas chromatography/mass spectrometry (GC/MS), and results from Lake Erie were confirmed using gas chromatography/triple-quadrupole mass spectrometry (GC/MS/MS). The chemical signals observed at the two sampling locations were different from each other primarily because of large differences in the sedimentation rates at the two sampling locations. HHCB was detected in the Lake Erie core whereas six compounds were detected in the Lake Ontario core. Using measured fragrance and 210Pb activity, the burden of synthetic musk fragrances estimated from these sediment cores is 1900 kg in Lake Erie and 18 000 kg in Lake Ontario. The input of these compounds to the lakes is increasing. The HHCB accumulation rates in Lake Erie for 1979-2003 and 1990-2003 correspond to doubling times of 16 +/- 4 and 8 +/- 2 years, respectively. The results reflect current U.S. production trends for the sum of all fragrance compounds.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".