Use of Epiphytic Diatoms in Cyperus Papyrus L. As Bioindicators in the Assessment of the Health of the Upper Euphrates River Between the Haditha Dam and Al-Baghdadi, Iraq
Bibliographic record
Abstract
Abstract The aim of this study is to use epiphytic diatoms in Cyperus papyrus L. plant as biological indicators for estimating the water quality of the upper Euphrates River between Haditha Dam and Al-Baghdadi. Biodiversity and biological indicators for water quality estimation, along with the Canadian Water Quality Index. The study showed that the water of the upper Euphrates River is warm, light alkaline, the electrical conductivity and the total dissolved soled of water affected by agricultural land water and human activities, turbidity, total hardness and the biological oxygen demand, chloride and sodium did not exceed the permissible limits, while the values of calcium, nitrate and phosphate exceeded the permissible limits. And that the calcium values have exceeded the magnesium values, and that the water in the river is well ventilated. We have identified 130 species of epiphytic diatoms in Cyperus papyrus L. plant, including 6 species (5%) belonging to the centrales diatoms and 124 species (95%) belonging to the pennales diatoms, and the highest total number of cells of the epiphytic diatoms was recorded as 1322.3 cells x 103 / gm in site I. The values of physical and chemical factors, ecological indices, and water quality index agreed that the water of the upper Euphrates River is of moderate pollution, medium biodiversity, mesotrophic, and homogeneous in the presence of species.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".