Avaliação das concentrações de metais pesados em sedimentos do Estuário do Rio Timbó, Pernambuco-Brasil
Bibliographic record
Abstract
Timbó River Estuary is located in the Metropolitan Region of Recife, among the cities Paulista, Abreu e Lima and Igarassu. \nIt has an approximate area of 1397 hectares, and is affected by human action, especially that related to urban pressure and industrial \nactivities. This work aims to determine the hydrological parameters and heavy metals concentrations (Zn, Mn, Cr, Cu, Ni, Cd and Fe), in rainy and dry periods. Hydrological parameters were measured at four points in the main channel of the river, according to Standard Methods for Examinations of Water and Wastewater. Sediment samples were submitted to acid process in a sample digester using the microwave and, for the quantification of metals, using the Optical Emission Spectrometer with Inductively Accolade Plasma (ICPOES). Results indicated that Timbó water is compromised concerning dissolved oxygen values (DO); and concerning dissolved oxygen saturation which indicated oversaturation in the most stations sampled. The maximum values of zinc (723 mg.kg-1), manganese (438 mg.kg-1), chrome (338 mg.kg-1) and iron (62840 mg.kg-1) were above those of reference, also presenting concentrations higher than the guide-values adopted by the Canadian Counselor of Environmental Minister. However, pH values (reduced conditions) and the organic load tend to immobilize metals in the sediment by adsorption and precipitation mechanisms making them less available to the \nother aquatic compartments.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".