Critical examination of soil metals distribution in the Copper Belt City of Lubumbashi (D.R. Congo): analysis of soil eukaryotic communities
Bibliographic record
Abstract
The main objectives of the present study are (1) To determine the dynamics of metal distribution around the main mining site in the Copper Belt City of Lubumbashi, and (2) to establish the soil eukaryotic profile in ecologically different sites. The highest levels of copper and cobalt were found at the remediated tailing and the mining sites with 9447 mg/kg and 1387 mg/kg for copper, and 2228 mg/kg and 817 mg/kg for cobalt, respectively. The total levels of these elements in urban areas located beyond 2 km from the mining site were, in most cases, low and below the levels expected to cause harm to the environment and humans. A close examination of the amplicon sequences revealed that Bigelwiella and Gymnochlora were among the top two most prevalent algae genera at each site. For metazoan populations, Mnemiopsis (48%) was the most dominant genus in the residential site, while Diadegma (41%) was the dominant genus in the agricultural dry land. Pseudosuccinea (23%) was predominant in agricultural wetland and Skrjabinema with 26% was the prevalent genus in the tailing. Soil metal content, pH and organic matter levels were not the driving factors of the variations in eukaryotic compositions and abundance.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".