Evaluation of Al-Shamiyah River water quality using the Canadian Council of Ministries of the Environment (CCME) water quality index and factor analysis
Bibliographic record
Abstract
ABSTRACT Canadian Council of Ministries of the Environment Water Quality Index (CCME WQI) was used to determine Al-Shamiyah River water quality and its suitability for aquatic life. To calculate CCME WQI, a set of sixteen water quality parameters were evaluated: water temperature (W.T), turbidity (Tur), total dissolved solids (TDS), pH, dissolved oxygen (DO), the biological oxygen demand (BOD5), chlorides (Cl), nitrite (NO 2 ), reactive nitrate (NO 3 ), reactive phosphate (PO 4 ), and dissolved heavy metals (cadmium, copper, chromium, zinc, manganese, lead). In addition, water samples were collected monthly from four sites along Al-Shamiyah River during the period from March 2013 to February 2014. According to CCME WQI analysis, the water quality of Al-Shamiyah ranged from 70.1 to 84.47 at the studied sites, which is considered “Fair–Good”,and was well above the “Marginal” class. The quality of the water is at a desirable level. The water quality seems unaffected by any pollutants that may have entered the river, and it remains at a quality necessary to sustain diverse and sensitive aquatic life. The results of PCA reflected a good look on the water quality monitoring and interpretation of Al-Shamiyah River water.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".