Bibliographic record
Abstract
Water is one of the most important inputs for economic development and sustainable development; as the demandincreases, so too does the importance of water. The future looks miserable if Egypt does not succeed in formulatingand implementing water resources management approach which can match the limited freshwater supply with theincreasing demand. This study intended to shed the light on the future water status in Egypt based on the currentstatus of the available water resources, the water demand, the institutional and legislative frameworks of watermanagement, adding to shed the light on the strategies and policies to rationalize water use and to augment watersupply. This study intended to explore how Egypt will safeguard its water resources in the future, both with respectto quantity and quality and how it will use these resources in the best way. Recommendations to help overcomeanticipated water challenges and to optimize the available opportunities were provided in this worthwhile study asknowledge of Egyptian water resource planning is presently very limited and largely undocumented. Hence, thechallenges and opportunities were discussed in order to support the decision-making process concerned withwater resources management as an essential prerequisite for Egypt sustainable development. The future scenariosthat introduce the future challenges, using the available opportunities, were investigated and recommendations tohelp overcome the future challenges were presented.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".