Metal Speciation and Contamination in Dredged Harbor Sediments from Kaohsiung Harbor, Taiwan
Bibliographic record
Abstract
The status of metal speciation and contamination of sediments in Kaohsiung Harbor, Taiwan, was evaluated by a five-step sequential extraction procedure (exchangeable, carbonate, Fe–Mn oxides, organic matter, and residual). Eleven dredged sediment samples from various locations in the harbor were characterized in terms of heavy metals, grain size, and total organic carbons. Results showed that Hg, Pb, Cd, Cr, Cu, Zn, Ni, and Mn had different species composition patterns. The degree of sediment contamination was determined for an individual contamination factor (ICF) and a global contamination factor (GCF); results showed that Kaohsiung Harbor had a high potential risk for Pb, Cd, Cr, and Cu. Based on GCF values, the results showed that those stations, located in the vicinity of the river mouth, fish port, and industrial sites, contributed high potential risk to Kaohsiung Harbor. The potential risk of heavy metals to the environment was assessed for risk using the risk assessment code (RAC) and results showed that Pb, Cd, Zn, and Mn generally created a medium to high risk, and Hg, Cr, Cu, and Ni generally created a low to medium risk.
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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 | 0.000 | 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".