Occurrence and Risk Assessment of PAHs in Surface Sediments from Western Arctic and Subarctic Oceans
Bibliographic record
Abstract
In the fourth Chinese National Arctic Research Expedition (from July to September, 2010), 14 surface sediment samples were collected from the Bering Sea, Chukchi Sea, and Canadian Basin to examine the spatial distributions, potential sources, as well as ecological and health risk assessment of polycyclic aromatic hydrocarbons (PAHs). The ∑PAH (refers to the sum of 16 priority PAHs) concentration range from 27.66 ng/g to 167.48 ng/g (dry weight, d.w.). Additionally, the concentrations of ∑PAH were highest in the margin edges of the Canadian Basin, which may originate from coal combustion with an accumulation of Canadian point sources and river runoff due to the surface ocean currents. The lowest levels occurred in the northern of Canadian Basin, and the levels of ∑PAH in the Chukchi Sea were slightly higher than those in the Being Sea. Three isomer ratios of PAHs (Phenanthrene/Anthracene, BaA/(BaA+Chy), and LMW/HMW) were used to investigate the potential sources of PAHs, which showed the main source of combustion combined with weaker petroleum contribution. Compared with four sediment quality guidelines, the concentrations of PAH are much lower, indicating a low potential ecological risk. All TEQPAH also showed a low risk to human health. Our study revealed the important role of the ocean current on the redistribution of PAHs in the Arctic.
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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 | 0.002 | 0.003 |
| 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) | 0.000 | 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".