A Comparative Assessment of River Water Quality in Mountain Regions of Russia and Armenia
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Bibliographic record
Abstract
The paper highlights results obtained from collation between river water quality in mountain regions of Russia and Armenia employing two different methodological approaches: a method of a complex assessment by hydrochemical parameters by a Specific Combinatorial Water Pollution Index (SCWPI) and the Canadian Water Quality Index (CWQI). Assessment was done of water quality of typical, identical in terms of conditions of formation small- and medium-size mountain rivers in Russia (river Terek basin: the Malka, the Baksan, the Cherek) and Armenia (rivers Kura-Araks basin: the Vorotan, the Voghchi, the Pambak). Collation was done between results of a complex assessment of water quality in mountain rivers obtained employing two indices: SCWPI and CCME WQI and two sets of norms: maximum allowable concentrations (MAC) set for fishery waters and ecological norms, and critical water pollution indices (CPI) and the highest excursive indices, defined. As shown, the river water quality classes by both indices coincide when using ecological norms, whereas difference in assessment results obtained through different methods employing common MAC set for fishery waters is primarily determined by more stringent values of MAC set for heavy metals. As an ultimate result, water quality in the studied rivers is characterized as marginal (the 4th class) for the Malka, the Baksan, the Cherek and the Voghchi and fair (the 3rd class) for the Vorotan and the Pambak. Methodological approaches to river water quality and pollution levels to be developed need to focus primarily on application of ecological (regional) norms or background hydrochemical parameters accounting for natural and climatic peculiarities of river watersheds.
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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 | 0.000 | 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 | 0.001 |
| 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 it