Evaluating of raw and treated water quality for some water treatment plants in Tikrit by Water Quality Index
Bibliographic record
Abstract
A water quality index is an essential part in the management system of water resources through to its use as a numerical scale to evaluate and classify the quality of water body for various beneficial uses (drinking, industry and irrigation). The present study used the Water Quality Index (WQI) based on Canadian Council of Ministers of the Environment, 2001 as a tool to evaluate the quality of raw and treated water for four water treatment plants in Salah Alddin province - Tikrit City form October 2010 to the end of January 2011. For this purpose, Eight variables were chosen which are: water temperature (˚C), turbidity (NTU), total dissolved solids (mg/L), pH, hardness (mg/L as CaCO3), calcium (mg/L), magnesium (mg/L) and chloride (mg/L). The study showed that the WQI values for raw water in all plants were classified as Category III (moderate) (65.56 - 75.6). Significant improvement in treated water was noticed for consecutive months (October and December and January ). For Tikrit and Ouja water plant the WQI values are ranging between (79 – 89.77) and (79.1 – 89.73) respectively. The corresponding values for Al-Qadisiyah and Al-Qadisiyah (Al-Faris ) are (79.56 – 89.59) and (79.04 – 89.6) which means that the classification of water is within the second Category (good).
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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 | 0.001 | 0.001 |
| 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".