Comprehensive Risk Assessment of Health-Related Hazardous Events in the Drinking Water Supply System from Source to Tap in Gaza Strip, Palestine
Bibliographic record
Abstract
Background: The traditional approach in the management of the quality drinking water, and relying on end-product testing, has proven ineffective in protecting public health. Therefore, the transition to a systematic approach in drinking water supply systems management from the source to the consumer tap was taken as a water safety plan (WSP). Objective: The study aims to investigate the health-related hazardous events in order to decide on the best risk-reduction strategies in the supply of drinking water in the Gaza strip. Methods: A semiquantitative matrix method for risk assessment was applied. Also, chlorine residual, electrical conductivity, and nitrate concentration further tested in 109 water wells, 109 small-scale water desalination plants, 197 tanker trucks, and 384 households distributed over five governorates of the Gaza strip. Results: , respectively. Furthermore, zero percent of water samples met the recommended criteria, indicating that the groundwater in the Gaza strip is nonpotable. Only 12.8% and 8.8% of water samples met the permissible levels at catchment areas and municipal water at household, respectively, indicating sever health impacts on the public. Moreover, the most hazardous events were related to high levels of groundwater salinity, the low level of disinfection, the effect of electricity outages on the efficiency of the desalination process, and leakage of water from the tanker truck tank reservoirs. Therefore, urgent interventions are required to improve the quality of water and to mitigate the possible health effects. Conclusion: The prioritization of hazardous events that are proportional to the degree of their attributed risk could help guide in making the right risk-reduction decisions. Urgent interventions are required to improve the quality of water and to mitigate the possible health effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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) | 0.000 | 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".