Study on Change of Quantity of Cultivated Land and Its Driving Forces in Sichuan Province in the Recent 15 Years
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
This paper takes the cultivated land in Sichuan Province as the research object based on the statistical data about cultivated land between 1995 and 2009, selects eight variable factors that affect change of the quantity of cultivated land, uses the principal component analysis to analyze the direct correlation between different factors, puts forward the two driving factors of economy and population and then sets up a binary regression model to make a quantitative analysis of the overall value of the principal component factors abstracted. The result shows that, the quantity of cultivated land in Sichuan Province has undergone a change process of slow reduction – sharp reduction – slow increase. Economic factor and population factor are the most important driving factors that affect change of quantity of cultivated land in Sichuan Province and they are both negatively correlated with change of cultivated land. The model shows that, the overall influences of these two types of driving forces are still constantly increasing, but influence of the economic driving force on cultivated land is weakened.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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