EVALUATION OF THE GROUNDWATER QUALITY IN GISHIRI VILLAGE – KATAMPE, ABUJA USING WATER QUALITY INDEX
Bibliographic record
Abstract
Water quality is inherently linked with human health, poverty reduction, food security, livelihoods, preservation of ecosystems, economic growth, and social development of societies. This study evaluated the groundwater quality of Gishiri-Katampe, Abuja-Nigeria using statistical and geospatial techniques for water quality indexing. The study also used hydro-chemical parameters, geographical information, and statistical analysis to assess groundwater pollution potential; identify the most vulnerable areas, and generate a groundwater quality map. The Canadian Water Quality Index, the GIS mapping of the water quality of Gishiri indicates that the Water Quality Index is within the range of 76.87 to 92.53. Similarly, the WQI is predominantly good (62%), indicating a minor degree of threat. However, 38% of the area is occasionally threatened (fair) on the Canadian scale. However, some areas are occasionally threatened (fair) with the corresponding WQI of 28% within the study area. Moreover, out of the 11 water quality parameters analyzed, 6 parameters (dissolved oxygen DO, turbidity, chemical oxygen demand COD, NO3, Na, and biological oxygen demand BOD) were identified as significant parameters as indicated by the correlation and regression analysis. This suggested that they strongly influenced the variability of the water quality.
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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 | 0.029 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".