Assessment of Water Quality at Al-Hammar Marsh before and after Flow Improvement
Bibliographic record
Abstract
Marshlands have been considered among the most productive ecosystems on Earth. Marshlands existingin Mesopotamia are recently acknowledged by the United Nations as one of the international heritage sites.The current research highlights the deterioration level in the water quantity of the Al Hammar marshwhich is one of the famous marshes in the south of Iraq. Recently, pipe culverts were constructed to reducethe salinity of the Al Hammar marsh. Data on Total Dissolved Solids (TDS), Electric Conductivity (EC), andPower of Hydrogen (pH) from February 2019 to February 2020 at five stations (distributed within Al Hammarmarsh) were used to assess the water quality before and after the construction of pipe culverts. Two standardswere used in the assessment: the Iraqi Water Quality Standard (IWQS, No.417) and the World HealthOrganization (WHO) Standards for drinking, irrigation, and aquatic life. In addition, the quality of ecologicalhealth in the Al Hammar marsh was assessed by using the Canadian Water Quality Index. Results showthat the quality of water in the Al Hammar marsh is not recommended to be used for irrigation while theaquatic life is at a threat level.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".