Metal Contents in Sediments (Cd, Cu, Mg, Fe, Mn) as Indicators of Pollution of Palizada River, Mexico
Bibliographic record
Abstract
Some heavy metals and trace metals reach aquatic ecosystems from natural and anthropogenic sources, and are considered some of the most important environmental contaminants due to their toxicity, persistence and tendency to accumulate in aquatic organisms. Thus, their study is needed due to the environmental risk they pose. Concentrations of Cu, Cd, Mg, Fe and Mn in recent sediments of the deltaic lagoon-river system of the Palizada river, Campeche, Mexico were determined for three climatic seasons on the 2010 annual cycle. The results confirmed that the climatic season has great influence over the results variability. The highest levels of Cu, Fe and Mn were found during dry season, which may suggest significant evaporation phenomena in the area. Both Fe and Mn are abundant elements in the Earth crust; their concentrations could be related to the study area’s characteristics, given the conjunction of two sedimentary provinces: terrigenous in the western portion and carbonated in the eastern. On the other hand, the results suggest a high relationship of Fe-Mn (r = 0.5131), Fe-clay (r = 0.5978), Cu-Mn (r = 0.8707), Cu-clay (0.8501) and Mn- clay (0.9311). The latter confirms the high dependence of these elements and the great affinity of some metallic elements for finer sediments. In conjunction, the climatic season and the sediment’s characteristics are essential for metal mobilization and transport. Likewise, the Cd and Cu levels reported are lower than international parameter, indicating value ranges ??that could cause effects in exposed organisms.
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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 | 0.000 | 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".