ANTHROPIC EVALUATION IN THE PARANÁ COAST THROUGH THE ION PHOSPHATE CONCENTRATION DETERMINATION IN WATER RESOURCES
Bibliographic record
Abstract
The increase in pollution in water resources comes from practically all human activities, whether domestic, commercial, or industrial. The environment cannot absorb all pollutants, as each of these economic activities generates specific pollutants, which have certain environmental implications and directly affect the quality of any water resource. Population growth is another factor that leads to an increase in the generation of waste, of which domestic sewage, rich in nutrients and, when deposited irregularly, causes an imbalance in the water body that can be highlighted. This study aimed to identify the concentration of the phosphorus element in the form of the phosphate ion in the water resources of the coast of Paraná. To quantify this element, the spectrophotometric method of molybdenum blue was used. Samples from ten points of continental waters in the coastal region were evaluated, which suffer a greater or lesser anthropic influence. Tests were carried out from August 2017 to May 2019. In the analytical methodology, solutions of ammonium molybdate, ascorbic acid, nitric acid, and glycerin were used. When these solutions are mixed in samples or standard solutions that contain the element phosphorus, there is the formation of the blue molybdenum complex. Five repetitions were performed in each of the samples so that, in the end, the average value of the measurements was obtained. It was observed that the phosphorus concentrations through the phosphate ion showed results above 0.150 mg L-1, the maximum value of this macronutrient in water samples, recommended by the legislation, except for the result obtained in point 8 in November, whose concentration was 0.08 mg L-1. The results showed, therefore, that there is pollution in the sampled continental waters. As a consequence, it is possible to highlight that the high concentration of phosphate ion in the samples comes from human action, especially in those rivers that are closer to urban contingents.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".