Decentralized Wastewater Treatment System Impact Assessment on Groundwater Resources: Case Study Dana Biosphere Reserve/Jordan
Bibliographic record
Abstract
Jordan is one of the world’s most water-scarce countries. Almost all of the water supply systems in Jordan depend on groundwater and springs which are highly depleted. While only 60 percent of households in Jordan are connected to the sewage systems. Hence, there is a significant, untapped potential for decentralized approaches for wastewater management. DWWTS are environmentally sound and sustainable technology can be used for suburban and rural communities such the ones found in the Dana Biosphere Reserve area. Groundwater contamination risk is the critical point when implementing wastewater treatment systems including DWWTS. DRASTIC Model, an inexpensive method for evaluating the vulnerability of groundwater resources to pollution based on hydrogeologic settings, was applied to assess the groundwater contamination vulnerability in the study area. The DRASTIC index value indicates that the potential for polluting groundwater is low. This study recommends implementing DWWTS to serve communities in Dana Biosphere Reserve area emphasizing the development of groundwater monitoring program during the operation of the facility.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".