CONCENTRATIONS OF Cd, Cu AND Zn IN SEDIMENTS COLLECTED FROM URBAN LAKES AT KELANA JAYA, PENINSULAR MALAYSIA
Bibliographic record
Abstract
Kelana Jaya Municipal Park is a popular recreation park in Petaling Jaya. The five lakes, located within the Park, were ex-mining ponds, functioning as flood retention ponds and receiving effluents from nearby human activities mainly from residents and transportation. A study was conducted to determine the distribution and sources of heavy metals (Cd, Cu and Zn) in the sediments of Kelana Jaya Lakes. Concentrations of Cd, Cu, and Zn for surface sediment were determined by using aqua-regia method and sequential extraction technique. Total Cd concentrations ranged from 0.48 μg/g to 2.68 μg/g dry weight (dw) for all lakes. Total Cd concentrations in sediment of all lakes exceeded CCME (Canadian Council of Ministers of the Environment, 2001) guidelines. Total Cu concentrations ranged from 7.37μg/g to 73.6 μg/g (dw). Only Cu concentration in one lake exceeded the CCME guidelines besides having the highest mean concentration among all. Total Zn concentrations ranged from 107 μg/g to 529 μg/g (dw). Again, The Zn concentrations in three lakes were found to exceed CCME guidelines for Zn concentration in freshwater sediment. Geochemical study on sediment revealed that nonresistant fractions for Cd, Cu and Zn for other lakes there Cu and Zn indicated that lakes in the park, especially near oxidation pond and monsoon drains, could have received anthropogenic metals from domestic wastes. Rehabilitation program and regular biomonitoring at Kelana Jaya Lakes are therefore recommended.
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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".