Water Quality Index, a Useful Tool for Evaluation of Danube River Raw Water
Bibliographic record
Abstract
The Danube River is the major source of drinking water supply for the cities in the southern part of Romania. The study was a descriptive-analytical one and lasted for 9 month. Samples were taken monthly between March 2016 and November 2016. Six sampling sites were selected to evaluate the spatial and temporal changes of water quality along the river. The samples were analyzed based on the standard methods for the following parameters: pH, conductivity (EC), NH4+, NO3-, Cl -, suspended solids, PO43-, SO42-, metals (Fe, Cd, Cr, Pb, Ni, Hg, As, Zn, Cu, Mn). The obtained values were compared with those imposed by the Romanian environmental legislation. An efficient and simplified method to express the quality of water used for consumption is provided by the Water Quality Index (WQI). WQI reflects the quality of water in a single value by comparing data obtained from the investigation of a number of physico-chemical parameters to the existing limits. The evaluation of water quality was performed using the Water Quality Index of the Canadian Council of Ministries of the Environment (CCME WQI). Water quality indices were classified as: excellent, good, medium, bad and very bad. The results indicated the water quality classification as �good� in all six sampling selected sites.
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How this classification was reachedexpand
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 | 0.004 | 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) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".