Heavy metal contamination of river sediments in Vietnam
Bibliographic record
Abstract
There are two rivers in Hanoi City, Vietnam, the To Lich and Kim Nguu rivers, which are the main sources of irrigation water for suburban agricultural land and feed water sources for fish farming ponds. Industrial wastewater that has been discharged into the rivers has degraded the quality of sediments in the river system. The present study showed that sediments in the To Lich and Kim Nguu rivers are heavily polluted with heavy metals. Metal concentrations in sediments appear to be closely related to the type of manufacturing plants located along the rivers. The heavy metals were bound with sediment particles in fractions such as the exchangeable, carbonate, oxide, organic matter and residual fraction. Total heavy metal concentration in the sediment was correlated with organic matter content for copper, lead and nickel while no correlation was found for cadmium, zinc and chromium. Ethylene diamine tetra-acetic acid caused high heavy metal leachability in comparison with water, acetic acid and nitric acid. Average potential leachability decreased in the order: cadmium > nickel > chromium > copper = zinc > lead. The leachability exhibited a tendency of decreasing with increasing organic matter for heavy metals other than chromium and zinc. To reduce the pollutants discharged from plants, countermeasures by the government and the technological improvement of wastewater treatment in manufacturing processes are needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".