The increasing water stress projected for China could shift the agriculture and manufacturing industry geographically
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The sustainable development of China has been challenged by the misalignment of water demand and supply across regions under varying climate change scenarios. Here we develop a water stress prediction index using a fuzzy decision-making approach, which analyzes spatiotemporal variations of water stress and concomitant effects on the populace within China. Our results indicate that water stress will increase from 2020 to 2099 under both low and high emission scenarios, primarily due to decreased water supplies like surface runoff and snow water content. Seasonal analysis reveals that annual fluctuations in water stress are mainly driven by changes in spring and autumn. Water stress is projected to be considerably lower in southeastern provinces compared to northwestern ones, where, on average, over 20% of the Chinese population could be severely impacted. These changes in water stress could lead to the north-to-south migration of the agriculture sector, manufacturing sector, and human population.
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.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it