Environmental Assessment Using Canadian Water Quality Index for Hilla River in Babylon Governorate, Iraq
Bibliographic record
Abstract
The goal of the current study is to use the Canadian Water Mechanism Manual to assess the water quality at five stations along the Shatt Al-Hilla river in the Iraqi province of Babylon.The current research demonstrates how the Shatt Al-Hilla River and five other locations in Babel City, Iraq, were evaluated using the Water Quality Index developed by the Canadian Council of Ministers of the Environment (CCME WQI).The fieldwork was finished in April 2019, between November 2018, and this month.The CCME WQI was built using thirteen factors for measuring water quality (chromium, chemical oxygen demand, lead, biological oxygen demand, dissolved oxygen, turbidity, sulphate, nitrite, nitrate, total hardness, total dissolved solids, pH magnitude and water temperature).The average magnitudes for five stations along the CCME WQI for the Shatt Al-Hilla River ranged from 61.94 to 81.93 depending on the index's findings.It was also noted that there is a variation in the studied physical and chemical properties of the samples taken from the five stations distributed along the Shatt al-Hilla River.These data show that the water quality for drinking purposes may be assessed as marginal in all sites, with the exception of station 1, where the water quality index was evaluated as good.In order to prevent pollution, conserve water, and achieve proper management, this study article underlines the need for substantial action to control river water 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".