Variations and ecological risk assessments of heavy metals in surface sediments from Guan River Estuary
Bibliographic record
Abstract
Heavy metal concentrations in surface sediments from Guan River Estuary were measured with ICP-MS and AFS.The results showed that the pollution of heavy metals has become more and more serious in recent years,especially Hg and Zn.Compared with other estuaries in China,Hg distributed a higher level,Zn the highest and Cr,Cd,Cu,Pb and As above the average level.The enrichment factor of Hg reached 3.44,indicative of potential new sources in this area.The higher concentrations of heavy metals were generally found at site H07 and decreased gradually around,which might be associated with the influence of entrance bar at Guan River Estuary.According to H kanson ecological risk index method,the average ecological risk of heavy metals in surface sediments from Guan River Estuary is at slight level.Assessments based on SQGs indicated that biological toxicity effects of different heavy metals might happen occasionally at different sites,in which,toxic effects of Zn at some sites might happen frequently.Risk assessments based on Sediment Quality Criteria(carried out in Canada) suggested that Zn,Cu and As were more likely to induce adverse biological effects,in which adverse effects of Zn might happen frequently.
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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".