Evaluación de la Variación de la Calidad del Agua en la Cuenca Alta del Río Pita.
Bibliographic record
Abstract
The moors are the main source of water supply in the Andean countries, so it is essential to evaluate the availability of this resource in terms of quality and quantity. The present investigation evaluated the space-time variation of the water resource quality and the quantity-quality relationship in the upper watershed of the Pita River (CARP), that with an area of 173 km2 is one of the main sources of water of the Metropolitan District of Quito (DMQ). Data of physical-chemical and microbiological parameters, flow, precipitation, and temperature were used, these are the product of the monitoring during 19 years, period 2000-2018, in five points distributed in the upper, middle and lower areas, the information was subjected to an exploratory analysis to obtain a solid and complete database. Water quality was determined through an index based on the methodology proposed by the Canadian Council of Ministers of the Environment (CCME), establishing quality criteria based on current environmental regulations, own watershed characteristics and additional studies, synthesizing the matrix of quality data in a single value and constituting a tool that allows a simple analysis for politicians, technicians, and the general public. The spatial analysis determined better quality water in the upper part, which deteriorates in the middle part and shows a slight recovery in the lower part. The quantity-quality relationship was determined through correlation and evidences the existence of partial interactions that increase in extreme seasonal and historical events. Finally, good water quality was determined in the first analyzed period that changed to regulate - acceptable in the second instance, returning quickly to good quality from the conservation actions carried out by the Public Metropolitan Enterprise of Water Supply and Sanitation of Quito (EPMAPS) and the National Water Fund (FONAG).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".