Ecological Sensitivity Assessment of Maqu Wetland in Upper Yellow River
Why this work is in the frame
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Bibliographic record
Abstract
Applying ecological factor scoring method and GIS spatial analysis function,this paper studied on the ecosystem sensitivity of Maqu Wetland in the Upper Yellow River. Based on the analysis of the six factors of the waters,grasslands,woodlands,topography,urban construction and transportation,it generated the ecological sensitivity zoning map of Maqu Wetland. Four levels of extreme sensitive area,high sensitive area,moderate sensitive area and low sensitive area were divided according to their ecological sensitivities. The results show that the extreme sensitive area and the high sensitive area are 81% of the total area of Maqu Wetland in the Upper Yellow River,which shows the environment is fragile and vulnerable to the destruction of human activity and the impact of climate change. So it should strictly control the development and utilization and focus on protection in the future.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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