Effectiveness of using palm fronds in reducing water evaporation
Bibliographic record
Abstract
One of the major problems in water resource planning and management is controlling of high evaporation from reservoirs, especially in arid countries such as the Kingdom of Saudi Arabia. Evaporation reduction can help in increasing water saving and thus reducing stress on water demand. Many types of water covers are internationally used to reduce evaporation from open water surfaces. Due to the large number of date palm trees in the Kingdom, a massive waste from these trees is disposed annually. Palm leaves as an agricultural waste can be converted to fronds and then used as a floating cover on the water surface to reduce evaporation. This paper presents feasibility results of testing palm fronds as covers in reducing evaporation from open reservoirs. Three pools were constructed at a selected site at King Saud University, Riyadh to prove the effectiveness of the proposed fronds. Data collected from the study site showed that evaporation reduction from the fully covered pool was about 55%, while that from the half covered pool was about 26%. Water quality analysis showed that the fronds have no serious effect on water quality. These results confirm the effectiveness of the fronds in evaporation reduction with no harmful effects on water quality.
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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 | 0.000 | 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 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".