Is a mussel processing site a point source of Zn contamination? evidence of Zn remobilization from boiled mussel, Perna viridis
Bibliographic record
Abstract
Sediment sampling in the Straits of Johore revealed that the surface sediments collected at a jetty near a mussel processing factory in Kg. Sg. Melayu had elevated Zn concentration in its first geochemical fraction; namely, easily, freely, leachable or exchangeable (EFLE) and its total concentration. This total Zn level in the sediment was comparable to the polluted sites on the west coast of Peninsular Malaysia. It was assumed that the tap water, in which mussels had been boiled, might have contained high levels of Zn which would then be released to the drainage system and finally emptied into the coastal waters where the jetty is located. In order to confirm this point source of Zn contamination, a laboratory study was designed to ascertain if the boiled mussels contained higher concentrations of metals compared to a control group. The laboratory results showed that distilled water, in which fresh mussel tissues had been boiled for 15 minutes, possessed significantly (P < 0.05) higher levels of dissolved Zn. In addition, Zn concentrations in the total boiled soft tissues and boiled shells of fresh mussel Perna viridis were significantly (P < 0.05) lower than the Zn levels before boiling, and this finding evidently showed that Zn in the mussel tissues was remobilized and thus released to the water. Therefore, these results supported the conclusion that the mussel processing factory at Kg. Sg. Melayu, which used tap water to boil the mussels before shucking, was a point source of Zn contamination in this area in the Straits of Johore.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".