Evaluating Surface Water Quality of Euphrates River in Al-Najaf Al-Ashraf, Iraq with Water Quality Index (WQI)
Bibliographic record
Abstract
The present study illustrates the rapid pollution of Euphrates River, inwards Al-Najaf Al-Ashraf governance (Al-Kufa River) in Iraq, which is one of the most important rivers in the region. The river faces formidable pressure due to encroachments, discharge of untreated domestic and industrial waste, drainage water from cultivated orchards, and dumping of solid waste. This study was conducted to assess the temporary and locative organic pollution in the region. Water Quality Index (WQI) of the Al-Kufa river was determined according to the Canadian Council of Ministers of Environment (CCME) method by calculating seven parameters (water temperature, DO, COD, EC, TDS, turbidity, and pH) in two sampling stations. Surface water samples were collected in a period of four months (September to December) in 2023. WQI level, correlation analysis between parameters, and Iraqi and CCME drinking water specification standards were employed to classify the surface water status. The results show that the ecological condition can be classified as marginal with WQI= 49 and poor with WQI= 42 in stations 1 and 2, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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".