Assessment of Groundwater Quality Changes in the Rural Environment of the Hungarian Great Plain Based on Selected Water Quality Indicators
Bibliographic record
Abstract
Abstract In the present study, changes in groundwater quality are assessed after the construction of the sewerage network, based on 3 water quality indices. Sampling took place before (2013) and after (2017, 2018, 2019) the establishment of a sewerage network in 2014. In the pre-sewerage period, strong pollution of the groundwater was detected. A total of 90% of the groundwater wells according to the water quality status by Brown, 70% of the wells according to the contamination index C d by Rapant, and 80% of the wells according to the Canadian Council of Ministers of the Environmental Water Quality Index were categorized in the “polluted” or “heavily polluted” categories. After the establishment of the sewerage, significant changes were observed. In 2017, the number of wells in category 5 indicating the most contaminated samples decreased significantly for all three indices, while the number of samples in categories “good” and “acceptable” increased. Discriminant analysis was performed to determine if pre- and post-sewerage samples could be separated. A total of 75.6% of the cross-validated values were successfully categorized into the appropriate category, which indicates a significant difference between pre- and post-sewerage. Based on point and interpolated maps, it was established that in 2013, all three indices showed the highest pollution in the inner and southern parts of the settlement, while the northern areas of the settlement were less polluted. Based on the indices, it was determined that the process of groundwater purification in the settlement has started, although it will continue for years to come.
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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 | 0.001 | 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) | 0.001 | 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 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".