On the Characterization of Dredged Marine Soils from Malaysian Waters: Physical Properties
Bibliographic record
Abstract
Every year, large volumes of dredged marine soils (DMS) are removed from Malaysian water. Dredging activity is needed to maintain and enlarge water bodies. DMS properties are varies depending to space, time and land uses in the watershed. DMS were also reported to be contaminated with chemical and biological contaminants, making the materials risky for reuse. Information on DMS properties, e.g. physical, chemical and biological properties is essential to the selection of a suitable reuse option. This study is focused on the characterization of Malaysian DMS for beneficial reuse. Three samples from different dredging sites and one sample of sediment as a control were used in this study. Physical properties of DMS from Malaysia water were identified and quantified. The DMS were classified as high plasticity clay (CH), high plasticity silt (MH) and low plasticity silt (ML) for Lumut, Melaka and Tok Bali respectively. The results showed that the DMS from different locations have different physical properties. Thus, the characterizations of DMS with regards of physical properties are significant in decision making either to be reused or disposed.
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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 | 0.002 | 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) | 0.001 | 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".