DETERMINATION OF WATER QUALITY STATUS THROUGH ASSESSMENT OF PHYSICOCHEMICAL PARAMETERS ALONG SELECTED LOCATIONS OF ARDA RIVER, BULGARIA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The physicochemical properties of river water are a key factor for assessing the quality state of a given aquatic ecosystem. Nowadays, the pollution of surface waters, including river systems is mostly related to the anthropogenic pressure exerted directly on them, or indirectly on the catchment area. The main goal of this article is to determine the water quality of the Arda River, the main tributary of the Maritsa River, Bulgaria, in a spatial and temporal aspect, through analysis and assessment of the physicochemical state of the river waters. Water samples were analysed for the period 2015–2023 at four points along the Arda River and 10 physicochemical quality parameters were analysed. In the article, a Canadian complex index for water quality assessment, comparative and graphical methods were applied. The study area was visualised using geographic information systems (GIS). According to the obtained results, the surface waters of the Arda river generally “maintain” a satisfactory quality status according to the norms. The most frequent are the excesses of the values registered above the norms (up to 10 times) for the physicochemical indicators nitrates (N–NO2) and total N. Exceeded reference values for orthophosphates (P–PO4), total N and total P, pH are less common. In addition, the obtained results can be used both in the preparation of specific policies for sustainable management and use of river waters in the Arda river basin, as well as serve as a good basis for further research.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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