Sensitivity of Asian dust storm to natural and anthropogenic factors
Bibliographic record
Abstract
The impacts of natural and anthropogenic factors on sand and dust storm distribution of 2001 in East Asia have been investigated by using the most up‐to‐date desertification map in China and desert reversal scenarios in natural precipitation zones. Here we show that although desertification in China has only increased total area of desert by ∼2%–7% since 1950s [ Zhong, 1999 ; Zhu and Zhu, 1999 ], it has generated disproportionably large areas with dust storm production potentials. Depending on the degree of desertification, newly formed deserts covered 15% to 19% of the original desert areas and would generate more dust storm, ranging from 10% to 40%, under the same meteorological conditions for spring 2001. Among the natural factors, the restoration of vegetation covers in the Chinese deserts within the 200 mm/y and 400 mm/y precipitation zones was found to decrease the surface mass concentrations by 10–50 % in most regions. It is also found that the contributions of surface concentrations from non‐Chinese deserts account for up to 60% in Northeast China and up to 50% in Korea and Japan.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".