Quantification of pharmaceuticals, personal care products, and perfluoroalkyl substances in the marine sediments of Puget Sound, Washington, USA
Bibliographic record
Abstract
Concentrations of 119 pharmaceuticals and personal care products (PPCPs) and 13 perfluoroalkyl substances (PFASs) in marine sediments measured throughout Puget Sound (n = 10) and Bellingham Bay (n = 30), Washington, USA, are reported. These data are among the first measurements of PPCPs and PFASs in marine sediments from the Pacific Northwest and provide a comparison to previous measurements of these chemicals in influent, effluent, and biosolids from municipal wastewater treatment plants throughout the region. The concentrations of both PPCPs and PFASs in sediments from Puget Sound and Bellingham Bay ranged from very low to non-detectable for most compounds. Only 14 of the 119 PPCPs and 3 of 13 PFASs were quantifiable in sediments. Diphenhydramine (an antihistamine) was most frequently detected (87.5% of samples), with a maximum concentration of 4.81 ng/g dry weight and an estimated mean detected concentration of 1.68 ng/g. Triclocarban (an antibacterial) was detected in 35.0% of the samples, with a maximum concentration of 16.6 ng/g dry weight. Perfluoroalkyl substances were detected in 2.5% of analyses. Perfluorobutanoate, perfluorooctane sulfonate, and perfluorooctane sulfonamide were detected in 7, 5, and 1 sample(s) each, respectively, with the highest concentrations observed for perfluorooctane sulfonate (1.5 ng/g). Detected concentrations were often highest within the industrial harbor in Bellingham Bay and near the cities of Seattle and Bremerton. Environ Toxicol Chem 2013;32:1701-1710. © 2013 SETAC.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".