The Effects of Polluted River Water to the Riverside Groundwater, Case in Niger River in Koulikoro
Bibliographic record
Abstract
Ground water demand is increasing in many African nations due to a number of factors. The growth of population, climate change, increase pollution of rivers, and insufficient number of purifying stations and waste water treatment (or almost nonexistent) have pushed to the water authorities for exploitation of underground water. These underground /groundwater have a relationship with surface water. Then what can be the effects of polluted River to its riverside groundwater? To explore the answer of this question and for the prevention sustainable and a better integrated management of water resources, we will do in-depth study on “the relationship between river water and riverside ground”. In Koulikoro region the results of this research show that Surface waters have poor bacteriological quality, the amount of total coliforms is very high, and accordingly Niger River’s waters are not allowed for consumption without treatment. However the river water can be safely used for laundry, bath, sports and recreation. Generally the Groundwater quality is good despite increased salinity has been observed sporadically. We found also that for the entire region of Koulikoro the average infiltration rate is less than 19.8% of the gross rainfall.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".