Comparing the Efficiency of River Water Quality Parameterization by Different Methods Under a Significant Human-Induced Impact
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Bibliographic record
Abstract
We examine the different approaches in assessing the water quality of water bodies located within the territories with a significant human-induced impact. The hydrological region of Norilsk was used as a test site. The data used in the analysis characterize the period between 2001 and 2003; however, they are still relevant because of a high level of human-induced impact on water bodies. For the purposes of parameterization, the water quality indices which are being most abundantly used in Russia and abroad were evaluated. Results from parameterizing the water quality, obtained by various methods and combined into an overall scheme, were used to generate the rating scale for assessing the hydro-ecological status of aquatic ecosystems. These calculations show that the method of Specific Combinatorial Water Pollution Index (SCWPI) established by the departmental standard of the Federal Service for Hydrometeorology and Environmental Monitoring of Russia (Rosgidromet) provides the most objective water quality assessment for water bodies experiencing a significant human-induced impact. Similar results also apply for water quality parameterization using the Canadian CCME WQI method, which is confirmed by the closeness of correlation between the values of these indices. According to the SCWPI method, in none of the streams was the hydro-ecological status assessed as “normal”. In the sources of four rivers, it was found to be close to class 1, and their hydro-ecological status was assessed as “risk”. The water in 11 measuring sections corresponds to quality class 3, or a “critical” status of the aquatic ecosystem. In 12 measuring sections corresponding mainly to the estuarine segments of the rivers and some brooks, the hydro-ecological status of the1 water bodies is characterized as “disaster”, i. e. the water pertains to quality class 4 and 5. Furthermore, in none of the water bodies under study is the environmental “catastrophe” not recorded.
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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 | 0.001 | 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