Analysis of virtual water consumption in <scp>C</scp>hina: using factor decomposition analysis based on a weighted average decomposition model
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Exploring the cause‐and‐effect relationship between economic sectors and water resources is important to C hina. This study implemented a factor decomposition analysis by weighted average decomposition ( WAD ) model on the changes of C hinese virtual water ( VW ) consumption between 2002 and 2007, which includes both direct water consumption (consumed to produce final products) and indirect water consumption (consumed to produce intermediate products). The change in VW consumption is decomposed into three determinant factors: technological effect, economic structural effect and the products' scale effect. The results show that the volume of VW consumption in C hina has decreased from 5.92 × 10 11 m 3 in 2002 to 5.17 × 10 11 m 3 in 2007, which is mainly because of the technological effect (−5.48 × 10 11 m 3 ). The increase in net VW exports is mainly due to the economic structure effect (6.19 × 10 9 m 3 ) and the fast growth of exports (3.49 × 10 10 m 3 ).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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