Attempts to Answer on the Origin of the High Nitrates Concentrations in Groundwaters of the Sourou Valley in Burkina Faso
Bibliographic record
Abstract
Within the framework of the contract of Sourou River, a survey of the groundwater quality was performed through 7 campaigns of water sampling and analysis from 2006 till 2012. The water samples resulted from 23 drillings and 9 wells located in the Sourou Valley. Among the analyzed physico-chemical parameters, the nitrates concentrations observed were worrisome. Out of 32 water sources, 14 (44%) supplied a nitrates content superior to the WHO threshold value for drinking water (50 mg NO3/L). Very high concentrations, superior to 500 mg NO3/L with a peak in 860 mg/L, were observed. Given the important variations observed from a sampling point to another, a generalized contamination of the total aquifer was not possible. An individual diagnosis allowed to identify the possible causes of this degradation. Several sources of contamination, in connection with the anthropological activities, were observed near the water facilities (drillings/wells): animal and human wild defecation, presence of nontight latrines, solid waste, wastewater discharges. It is also advisable to wonder about the impact of the dynamite use for digging wells, this one being able to leave nitrates in the water. With regard to the intensive use of water from the strongly contaminated wells and drillings by the rural populations of Sourou, implementing protection areas within which would be eliminated the sources of contamination in addition to health education among populations could improve the situation. Care should also be taken in the use of nitrates explosives for digging new wells or drillings.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".