Assessment of Lake Water Quality in Central Serbia—Using Serbian and Canadian Water Quality Indices on the Example of the Garaši Reservoir
Why this work is in the frame
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Bibliographic record
Abstract
The water quality in lakes and reservoirs is crucial for maintaining ecological balance and ensuring public health. This research focuses on the water quality evaluation of Garaši Reservoir in Serbia, a vital source of drinking water for surrounding communities. We systematically analyzed three profiles (A1, B1, and C1) at various depths ranging from 50 cm to 1500 cm between 2021 and 2023. The study employed the Serbian Water Quality Index (SWQI) and the Canadian Water Quality Index (CWQI) to evaluate the water quality. The findings revealed significant spatial and depth-dependent differences. Higher concentrations of Aluminum (Al), Mercury (Hg) and Manganese (Mn), influenced by the inflow from the Velika Bukulja River, resulted in reduced overall water quality and suitability for drinking water. Dissolved Oxygen levels decreased with depth, indicating thermal stratification and nearly anoxic conditions, which are harmful to aquatic life. Some shallow areas exhibited poor water quality for recreational use due to high pH and metal concentrations. The study underscores the necessity of continuous and comprehensive monitoring to identify pollution sources and implement mitigation measures. Such efforts are essential to protect biodiversity and ensure the sustainable management of water resources in lakes and reservoirs.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it