Diagnóstico Preliminar de la Presencia de Metales Pesados en cinco (5) Ríos de la Provincia de Cotopaxi en el período 2022-2023.
Bibliographic record
Abstract
Water is essential for life since it is of great importance for the development of societies, In addition to having unique properties, and covers more than 70% of the extension of the planet, one of the main problems worldwide that is affecting the Environment is the pollution of Water Resources, producing negative aspects to the quality of water in rivers that are deteriorating due to the presence of pollutants From both natural and anthropogenic sources this is due to untreated water. The present research project aimed to evaluate the presence of heavy metals and their relationship with the physical, chemical and biological parameters existing in the rivers of the province of Cotopaxi these were: Río Cutuchi, Río Blanco, Río Pumacunchi, Río Illuchi, Río Calope. The methodology used was through a study to know the state of the water through the evaluation of 8 physical-chemical, biological and heavy metal parameters. To take measurements of the physical-chemical parameters, a multiparameter was used, which helped us obtain values of the parameters pH, temperature, dissolved oxygen, electrical conductivity in the three points designated for each river. Regarding the biological parameters and special metals for the collection of samples, the current water quality regulations NTE-INEN 2169 were taken as a reference, 3 points were determined with their respective coordinates for each river with a total of 15 water samples. Once the water samples were collected with the indicated protocols, they were sent to the laboratory for their respective analysis. Once the values of all the evaluated parameters were obtained, they were compared with tables 3 and 4 of Ministerial Agreement 097 A Annex 1 water quality criteria for agricultural use, in order to verify if they meet the water quality levels established in these tables. To determine the quality of water, the Canadian Water Quality Index (WQI Canadian) was applied, which allowed to evaluate and report on the quality of water resources, as well as for the correlation of physical, chemical, biological and special parameters, amoeba diagrams were graphed that allowed estimating the relationship between the sampling points and the parameters analyzed, technological tools were also used for the realization of the map. Interactive that helped to identify, the geographic information of the rivers, which indicates the water status of each river already mentioned. The analyzed results of the selected rivers allowed to appreciate the current quality of the rivers Cutuchi, Illuchi and Calope which indicate that it has a good water quality, having a value of 92.39, The Blanco river showed a favorable water quality with a value of 72.83. while for the Pumacunchi river it is found that it has a value of 37.41 having a bad water quality.
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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 | 0.002 | 0.002 |
| 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) | 0.001 | 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".