Trace elements in an adjacent channel of an anthropized area: a case study of Baixada Santista, Southeastern Brazil
Bibliographic record
Abstract
In recent decades, due to intensive industrialization, the Baixada Santista has undergone an intense process of environmental degradation. The metals are toxic and persistent in varying concentrations and oxidation states and may be incorporated in sediments and biota. Thus, understanding the importance of this contamination is necessary for coastal planning. This study provides a basis for understanding the levels of metal and As contamination in the Bertioga Channel (SP). The levels of Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Sc, V and Zn in superficial sediment samples were determined by ICP-OES. The degree of sediment contamination was evaluated according to the sediment quality standards set by the Canadian environmental agency (ISQG and PEL) and by statistical tests. All values were below PEL, and most of the sample values were below ISQG, except for As, Cu and Pb. From a cluster analysis, it was possible to differentiate eastern and western parts of the channel due to their distinct hydrodynamic patterns. Furthermore, it was possible to separate the trace elements by geochemical behavior, in which Cu, Pb and Zn were linked to a small anthropogenic contribution. Thus, this study detected small anthropogenic contributions from an adjacent channel of an anthropized area, but most of the results were linked to natural geochemical processes.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".