Water quality assessment in Morocco’s Inaouen basin
Bibliographic record
Abstract
The availability of clean water and sanitation has become a significant challenge in many regions worldwide, particularly in Morocco, due to harsh climate conditions and river pollution. This increases the water’s vulnerability to contaminants and heightens the population’s risk of waterborne diseases. The main objective of this study is to assess the impact of anthropogenic activities on the water resources and public health, as well as to evaluate the spatial distribution of certain chemical elements in the surface and groundwater of the Inaouen basin. The study primarily focuses on analysing the water’s physicochemical and bacteriological parameters. The spatiotemporal and multidimensional analysis conducted between 2021 and 2023 revealed a progressive increase in organic and mineral loads over time. The study also identified certain sections of the river with questionable health status, classifying them as having very poor water quality. Bacteriological analysis reveals severe groundwater pollution, with high levels of total coliforms, faecal coliforms, and faecal streptococci, indicating significant faecal contamination. This study suggests that the use of groundwater from these aquifers could pose a significant long-term health risk to the inhabitants of this watershed and increasing quality control of these waters.
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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 | 0.001 |
| 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".