Heavy metals (Pb and Cd) contents in the seawater and sediment in Panjang and Pamujaan Besar Islands, Banten Bay, Indonesia
Bibliographic record
Abstract
Abstract The industrial activities in the coastal area of Banten Bay harmed water quality and tourism aesthetics. This study aims to determine the accumulation of heavy metals Pb and Cd in the water and sediment, which was conducted for 3 months from May until July in 2019 in Pulau Panjang and Pamujaan Besar. Data were collected by using the purposive sampling method. The water samples were studied using Van Dorn Water Sampler, while sediment samples were undertaken using Peterson Grab. The concentration of Pb and Cd in water and sediment were analyzed at the Environmental Laboratory of the Department of Aquaculture. Those Concentrations in waters and sediments were the highest in June than in other months. In general, the water quality was still classified as normal because it was under the quality standards of the Decree of Ministry of Environment No. 51 of 2004. Heavy metal in Banten Bay fluctuated while Pb exceeded the quality standard in June and decreased in May and July. While Cd metal in May and June exceeded the quality standard and then declined in July. Those concentrations were still below the standard limits of the Canadian Council of Ministers of the Environment 2001.
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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 | 0.001 | 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) | 0.001 | 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".