Applying of Canadian water quality index for evaluation of some water treatment plants in Basrah province
Bibliographic record
Abstract
Abstract In this study, ten water treatment plants were evaluated for water quality for drinking by using the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI).The ten main water treatment plants were Jubyla(1), Khor Al Zubair, Al-Shaibah, AlmahkalAljadeed, Hay Al-Hussain, Al Asmaei, Al Garma(1), Al Abass, Al Madena Al Riadia, and Mhaijran. These water treatment plants were in different places in Basrah province and supply most of the needed water for citizens in Basrah city. The samples were collected for the treated water monthly from January to December of 2019. 13 parameters of the treated water were tested, which were the Turbidity (Turb), Total hardness (TH), pH, Total dissolved solids (TDS), Total suspended solids (TSS), Chloride (Cl-), Magnesium (Mg +2 ), Sodium (Na + ), Potassium (K + ), Calcium (Ca +2 ), Alkalinity (Alk.), Sulfate (So 4 ) and Electrical Conductivity (EC) for all stations. The CCME WQI method classified the treated water of Mhaijran station as poor which means is not suitable for drinking purposes and this is because of several reasons, such as the discharges of the pollutants into Shatt Al-Arab River from domestic, agricultural drainage, and industrial process pollutants. The water quality for the two water treatment plants, that are Al-Shaibah and Al Madena Al Riadia, were in good condition in the dry season. Whereas in the wet season, Al-Shaibah was marginal and Al Madena Al Riadia was fair. Al Abass was nearly fair in the dry and wet season whereas the others were ranged from marginal to poor condition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".