Appraisal of groundwater suitability and hydrochemical characteristics by using various water quality indices and statistical analyses in the Wadi Righ area, Algeria
Bibliographic record
Abstract
ABSTRACT This assessment research focuses on the hydrochemical characteristics and groundwater suitability in the Wadi Righ region, in southern Algeria. The statement of the problem revolves around determining water quality using various indices including Permeability Index (PI), Residual Sodium Carbonate (RSC), Water Quality Index (WQI), Sodium Percentage (Na%), Sodium Adsorption Ratio (SAR), Canadian Council of Ministers of the Environment's Water Quality Index (CCME WQI), Magnesium Hazard (MH), Irrigation Water Quality Index (IWQI), and Kelly Index (KR). Additionally, statistical methods were utilized to establish correlations between these indices and chemical elements. The working method involved investigating hydrochemical parameters in Wadi Righ's groundwater and analyzing 52 samples. The results indicate that water quality, as assessed by the water quality indices, was categorized as very poor and unsuitable overall, with lower quality observed particularly in the central and southern regions. However, groundwater demonstrated excellence and suitability for irrigation purposes. Qualitatively, the findings suggest that there are significant relationships among irrigation suitability indices, as indicated by Pearson correlation analysis. These relationships stem from shared inputs and hydrogeochemical characteristics of groundwater. This analysis reinforces the quantitative findings and provides insights into the underlying factors influencing groundwater quality and suitability for irrigation in the Wadi Righ region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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".