Investigating the hydrogeology of a water-supply area using direct-current vertical electrical soundings
Bibliographic record
Abstract
Abstract The drinking water of Budapest (Hungary) is supplied by wells located along the Danube River. In one of the water-supply areas, groundwater polluted by nitrate flows from the upper terrace of the river toward the lower terrace and the production wells. In order to protect the wells from pollution, the waterworks of Budapest has to know the hydrogeology of the area in detail. Since groundwater flow strongly depends on the type and distribution of the subsurface materials, we made 230 dc vertical electrical soundings (VES) in the lower terrace over an area of 6 km2 to map the subsurface conditions. There is a 200–300-m-wide high-resistivity zone (200–400 ohm-m) running parallel to the river and separated from the upper terrace by a 200–500-m-wide low-resistivity zone (<50 ohm-m). The low resistivity is due to silty and clayey sand, as indicated by monitoring wells. These sediments have low hydraulic conductivity; therefore, they form a hydraulic barrier against the polluted groundwater flow coming from the upper terrace. Except in the northern part of the area, they protect the lower terrace. In the northern part of the area, the lower terrace is narrow, and the low hydraulic conductivity zone is not well developed. Therefore, the polluted groundwater can seep through the lower terrace and reach the production wells. One-dimensional vertical electrical soundings can still be successfully used to map the shallow subsurface resistivity conditions over a large area. The results of the soundings greatly contribute to the understanding of the hydrogeology of the area.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".