Evaporation Retardation by Monomolecular Layers: An Experimental Study at the Aji Reservoir (India)
Bibliographic record
Abstract
It is an established fact that huge quantities of water are lost from lakes, reservoirs and soils by evaporation. This assumes greater significance in arid and semi-arid regions around the globe when a general scarcity of water is compounded by high evaporation loss from the open water surfaces of lakes and reservoirs. The use of surface covering by a monomolecular film to reduce evaporation loss from large open water surfaces offers the greatest promise among all currently available techniques. This is the only system that retains the water surface in a state that does not interfere with other uses of the body of water such as boating, navigation recreation, fish, and wildlife propagation. Various experiments and field trials worldwide have proven conclusively that the fatty alcohols and their emulsions effectively retard water evaporation and result in saving to the tune of about 20% to 50%. An experiment was carried out at the Aji Reservoir (India) using a mixture of Cetyl and Stearyl alcohol that confirmed 19.26% saving in evaporation loss. During this six-month trial, about 0.18 mcum of water was saved which otherwise might have evaporated.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".