Evaluación de la calidad del agua en la microcuenca del río Pumacunchi, provincia de Cotopaxi, periodo 2022
Bibliographic record
Abstract
The contamination of rivers is a worldwide problem, requiring the application of indices that help determine the quality of the water. The present investigation is oriented towards the evaluation of the water contamination of the Pumacunchi river through the CANADIAN and ICOMI indices for the period from May to July 2022. The parameters considered were: pH, turbidity, arsenic, iron, BOD, COD, fecal coliforms., conductivity, hardness and alkalinity, evaluated at two strategic points located in Chantilín-Saquisilí and Latacunga Wholesale Market. For the CANADIAN index all the parameters were produced, while for the ICOMI index the last 3 parameters considered were handled. The results allowed us to identify that, of the 10 evaluating parameters, only the pH and total hardness are within the Maximum Permissible Limit (LMP) established by the TULSMA for water for human consumption and irrigation. While electrical conductivity (694.50 uS/cm), arsenic (0.262 mg/L), iron (5.36 mg/L), BOD (8.19 mg/L), COD (35.17 mg/L), fecal coliforms (138166.66 NMP/100ml) and turbidity (138.22 NTU), exceeded the LMP in the criteria for water for human consumption established by the WHO and the TULSMA in the same way for irrigation water, except for the conductivity remains within the LMP. The CANADIAN index shows that the water quality of the Pumacunchi River is "Bad", for water for human consumption at the two photography points, with an average of 25.5 at point 1 and 20.3 at point 2, while for water irrigated land is also not suitable with an average of 48.8 (point 1) and 39.4 (point 2). In turn, the ICOMI index confirms that the water is of poor quality at the two points of the river with an average of 0.8 (point 1) and 1 (point 2). That is, the river water is not suitable for human consumption, nor for irrigation. These values are quite significant, due to the development of anthropic activities such as the discharge of wastewater without prior treatment, the grazing of animals, etc., which are carried out around it and altering the quality of the water.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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 teacher head, 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".