Integrated Water Quality Assessment in Damietta Branch Intakes at Dakahlia Governorate, Egypt
Bibliographic record
Abstract
The water quality of the Damietta branch evaluated and assessed using the water quality index (WQI), including twenty-one physical, chemical, and biological parameters (Temperature, Turbidity, Chlorine, Electrical Conductivity, Total Dissolved Solids, pH, Chloride, Total Alkalinity, Total Hardness, Dissolved Oxygen, Chemical Oxygen Demand, Biological Oxygen Demand, Nitrogen, Sulfate, Calcium, Total phosphorus, Sodium, Potassium, Nitrate, Magnesium, and Total Coliform) measured at eleven different drinking water intake stations in Dakahlia governorate along the Damietta branch of the Nile river for four successive years from 2018 to 2021. The scale for evaluating the water quality of the Damietta branch of the Nile River is created using the tolerance limits of Egyptian law “regarding the protection of the Nile River and waterways from pollution”, Law No. 48/1982, and its regulations No. 92/2013. The water quality index approaches: Weighted Arithmetic (WA-WQI) and the Canadian Council of Ministries of the Environment (CCME-WQI) are used to find WQI in Dakahlia Governorate along the stretch of the Branch. The Damietta branch of the Nile River indicates good and excellent suitability for surface water use according to the tolerance and permissible limits of Egyptian law and regulations.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".