Bibliographic record
Abstract
The WorldWater system dynamics model has been developed for modeling the global world water balance and capturing the dynamic character of the main variables affecting water availability and use in the future. Despite not being a novel approach, system dynamics offers a new way of addressing complex systems. WorldWater simulations are clearly demonstrating the strong feedback relation between water availability and different aspects of world development. Results of numerous simulations are contradictory to the assumption made by many global modelers that water is not an issue on the global scale. Two major observations can be made from early simulations: (a) the use of clean water for dilution and transport of wastewater, if not dealt with in other ways, imposes a major stress on the global world water balance; and (b) water use by different sectors is demonstrating quite different dynamics than predicted by classical forecasting tools and other water-models. Inherent linkages between water quantity and quality sectors with food, industry, persistent pollution, technology, and non-renewable resources sectors of the model create shoot and collapse behavior in water use dynamics. This paper discusses a number of different water-related scenarios and their implications on the global water balance. In particular, two extreme scenarios (business as usual - named "Chaos", and unlimited desalination - named "Ocean") are presented in the paper. Based on the conclusions derived from these two extreme cases a set of more moderate and realistic scenarios (named "Conservation") is proposed and their consequences on the global water balance are evaluated.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".