Heavy Metals in Surface Sediments of the Coastal Area Around Daerah Istimewa Yogyakarta, Indonesia: Their Relations to Land-Use Types
Bibliographic record
Abstract
The province of Daerah Istimewa Yogyakarta (DIY) has experienced significant changes in urbanization, industry, and tourism, making it one of Indonesia's fastest-growing areas. Increased anthropogenic activity in the coastal region may cause heavy metal contamination in that zone to grow. Based on different land-use types, this study examined the distribution of heavy metals, namely cadmium (Cd), lead (Pb), copper (Cu), and zinc (Zn), in surface sediment. It assessed the feasibility of sediment quality standards based on the Canadian Sediment Quality Guidelines (CSQG). Nine stations made up the sampling site, each representing a different land-use type, including mangrove ecosystem, tourist attraction, airport, harbor, mining area, bare land, shrimp pond, agricultural land, and settlement. The concentrations of Cd in bare land, shrimp pond, agricultural land, and settlement (with values of 2.707, 2.955, 2.983, and 2.873, respectively), and Cu in the mangrove ecosystem (with values of 42.893) slightly exceeded the corresponding Threshold Effect Level (TEL) value of CSQG. Meanwhile, the content of other heavy metals in all land use types tends to be low, even below the Limit of Detection (LOD). The data on the level of heavy metal pollution in the study area shows no connection between heavy metal contamination and different land-use types. It is brought on by a variety of circumstances, such as the fact that human activity in the study area did not significantly contribute to heavy metal contamination or that heavy metals were contaminated and then spread to other forms of land-use types, in this case, the mangrove ecosystem, by runoff and wind. This is because variations in salinity, estuary flushing, physical mixing and dilution, and chemical processes, including sorption, complexation, cation exchange, and redox reactions, all affect how heavy metals are transported by water. The government should create environmental regulations, laws, quality norms and standards, more funding for cutting-edge scientific research, and technical tools to prevent heavy metal pollution in coastal areas.
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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 | 0.001 | 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".