Assessment of Quality Indices of Drinkable Water Sources in Dumne, Mboi and Zumo of Song Local Government Area, Adamawa State using CCME Method
Bibliographic record
Abstract
The study explored water quality index of three drinking water sources (borehole, well & rivers water) from Mboi, Dumne and Zumo communitie, Located in Song Local Government Area, Adamawa State, Nigeria. Physicochemical parameters examined for the analyses are temperature, electrical conductivity (EC), total dissolved solids (TDS), hardness, calcium concentration, sulphate ion concentration, magnesium concentration, turbidity, total suspended solids (TSS), alkalinity, chloride ion concentration, nitrate ion concentration, fluoride ion concentration, Dissolved Oxygen (DO), Biological Oxygen Demand (BOD) and pH. These parameters were determined using various standard experimental procedures and tools. Water quality indices were evaluated using Canadian Council of Ministers of Environment (CCME) methods. Water quality indices obtained from this research investigation showed that the borehole, well and river water from the study areas are in good condition in line with the CCME rankings. From the result obtained, the WQI of borehole water of Mboi, Dumne and Zumo are 85.45, 88.76 and 88.91 respectively while the WQI of the investigated well water are 79.73, 85.42 and 82.77 respectively. The WQI for the river water of Mboi, Dumne and Zumo was found to be 71.86, 79.56 and 76.15 respectively. Based on CCME rankings, the three water sources investigated across the three research areass are good for human use and consumption and the rating of the water quality indices are as follow: Borehole > Well > River.
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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 | 0.002 | 0.002 |
| 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".