Evaluation of the Level of Pollution by Heavy Metals of Market Garden Soils along the Chari River in Ndjamena: Case of the 9th and 7th Districts
Bibliographic record
Abstract
The main aim of this study was to characterize the metal content of soils used for market gardening along the Chari river: the 7th and 9th districts of NDjaména. To achieve this, two sites were selected: Gassi and Walia, and two control sites (Gassi and Walia). A total of fifty (50) soil samples were taken (24 from the Gassi site, 24 from the Walia site and 2 as control soils) and then analyzed to determine a number of physico-chemical parameters (pH, OM and electrical conductivity) and heavy metal concentrations in the various soils. The TME content (As, Cd, Cu, Cr, Ni, Pb, Hg and Zn) of the soils was determined by plasma-coupled Atomic Emission Spectrometry. In order to assess the level of contamination in Gassi and Walia soils, the geoaccumulation index (GeoIndex), contamination factor and degree of contamination were calculated. Results for physico-chemical parameters revealed that pH ranged from acidic (4.6) to moderately neutral (6.5), electrical conductivity was higher in cultivated soils (mean 292.14 μs/cm) than in control soils (mean 149.33 μs/cm), and soils were rich in organic matter. Overall, heavy metal concentrations in cultivated soils were higher than in control soils. The pollution estimate shows that soils in the area have no moderate contamination. The increase in TME concentrations in cultivated soils is thought to be due to the input of agricultural inputs to the soil. However, these levels are below the Average shale reference and Canadian guidelines for agricultural soil quality. Principal component analysis shows that metals are positively and significantly correlated with each other, and negatively and moderately significantly correlated with each other.
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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 | 0.001 | 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".