Deserticulture Contributes to Targeted Poverty Alleviation Part I: An Advance Planting Test in Mu Us Sandy Land
Bibliographic record
Abstract
Nowadays, Chinese government is actively advancing the targeted poverty alleviation on a countrywide scale. It is difficult to conduct in some areas e.g. sandy land region and some arid and semi-arid region where the water is a shortage. In these areas, it is more important to solve ecological environment question than developing agriculture. So, to find some economic forest species that held certain ecological function of sand protection was in urgent need. Cerasus humilis, which has good health function and excellent in cold-resistance and drought-resistance, was introduced to Mu Us Sandy land. In this study, we found that this kind plant could well adapt to the sandy climate and bears fruit. In the future, the targeted poverty alleviation in the rural areas of northern Shaanxi will be based on planting Cerasus humilis gradually.
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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 | 0.002 | 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 | 0.001 | 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".