Metals, trace elements and ecotoxicity in sediments of the Cubatão River, Brazil
Bibliographic record
Abstract
The Cubatão River is one of the most important waterways of the coast of São Paulo. The continuous discharge of domestic and industrial effluents into the river and its tributaries resulted in loss of water quality across the system. Industrial and domestic landfills are also located around the studied area. The purpose of this study was to assess two aspects of sediments from the river and two of its tributaries (Perequê and Pilões Rivers): presence of trace elements and toxic metals, and ecotoxicity. Four sampling surveys were conducted from 2010 to 2011 on six different sites (here named P0, P2, P4, P5, P7 and P8). Ecotoxicity was assessed by exposing Hyalella azteca to the collected sediments. Instrumental Neutron Activation Analysis (INAA) and Atomic Absorption Spectrometry (GF AAS and CV AAS) techniques were applied for measuring concentration of metals and trace elements. The latter enabled quantification of Cd, Pb and Hg, while the former enabled quantification of a wide range of metals and trace elements. As, Cr and Zn concentrations obtained by INAA as well as AAS results were compared to threshold effect levels (TEL) and probable effect levels (PEL), the sediment quality guidelines proposed by the Canadian Council of Ministers of the Environment (CCME) for evaluating the potential effects on aquatic organisms. Cd and Hg values did not exceed TEL at the most of samples. Pb exceeded TEL at only one site campaign. As, Cr and Zn values exceeded TEL in most of sampling sites, with P2 and P4 showing the highest concentrations.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".