Surveillance of Heavy Metals Using Atomic Absorption Spectroscopy in the Lagoon La Escondida in Reynosa City, Mexico
Bibliographic record
Abstract
The concentration of heavy metals such: Arsenic (As), Lead (Pb), Cadmium (Cd), Mercury (Hg) and Chromium (Cr) was determined in water and sludge of the lagoon La Escondida in Reynosa city on the northeastern part of Mexico by the border with USA. The detection limits by Atomic Absorption Spectroscopy (DL, μg mL-1 ) were 0.05 for As; 0.10 for Pb; 0.10 for Cd; 0.05 for Hg; and 0.30 for Cr in water. The detection limits (DL, μg g-1 ) were 1.0 for As; 10.0 for Pb; 2.0 for Cd; 0.02 for Hg; and 6.0 for Cr in sludge. The objective of this work was to know the levels of these contaminants in this lagoon, since it is surrounded by a highly populated area of the city, besides it is considered as a natural protected resource, in which migratory birds coming from Canada and North America in the winter stop, rest and nest for some time. Nine samples of water and seven samples of sludge from different points, evenly distributed at the lagoon were taken and analyzed; the sampling places were chose according to the currents, influents and effluents of this body of water. The levels of these contaminates were found to be under the detection limits, except for mercury in a single sampling place, which come to be 0.23 μg mL-1 in a sludge sample. This is indicative of water contamination for heavy metals which requires further studies to establish the source and impact of this contamination.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".