The modified Canadian water index with other sediment models for assessment of sediments from two harbours on the Egyptian Mediterranean coast
Bibliographic record
Abstract
In this research, the modified Canadian water quality index (MCWQI) was successfully applied with other common sediment indices for quality assessment of sediments from two Egyptian Mediterranean harbours: Port Said (PS), and Damietta Harbour (DH). The geochemical analysis demonstrated the dominance of the sandy-mud texture for PS sediments, while it was muddy for DH sites. Organic carbon, and total phosphorus in DH (0.46%; 1.08%) were slightly higher than in PS (0.32; 1.07%), while total carbonate was higher in PS (12.12%) compared to DH (10.63%). Eight heavy metals (HMs) showed a similar order of abundance with higher records in DH for HMs (except Pb). Ecotoxicologically, HMs levels were lower than the effects range low (ERL), suggesting no adverse effects; however, Ni and Cr might cause impacts up to 40 - 90% (> effects range median; ERM), particularly in DH. Environmental indices (e.g., MCWQI) revealed that sediments of DH were more contaminated than PS, with a marginal (∼ 59%) and a fair (∼ 70%) quality, respectively. Statistically, good correlations with a noticeable trend of loadings among studied parameters were recognized in PS, compared to DH. The study emphasized the vital roles of the topography, current movement, and levels of activities, that control the distribution of contaminants, pollution status and hence sediment quality.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".