Dynamic evolution of land use structure in undeveloped areas of western China——A case study of Gansu Province
Bibliographic record
Abstract
Based on the land use data of Gansu Province in 1997 and 2008,the information entropy,Lorrenze Curve and Gini Coefficients were used to analyze the land use structure.The results showed that the distribution of different land use types was temporally and spatially unbalanced,had low order degree,and the land use structure was poor.The dynamic evolution of information entropy had gone through two stages in the region,that was,1997～2002 slowly growing stage,and 2002～2008 quickly growing stage.Overall,information entropy in the southeast was higher than in northwest.The land use structure was single.By the Lorenz curve and Gini coefficient analysis,the unbalanced degree of the cultivated land and woodland decreased,but the gaps between regions were still large.While that of the garden plot,grass,traffic,water and unused lands exhibited an opposite trend.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".