Thought on Giving up Farming and Returning the Wood (grass): taking the passage west of the Yellow River as an example
Bibliographic record
Abstract
As the transitional part between oasis and desert, giving up farming and returning the wood (grass) in the edge of the desert can prevent sand dune effectively and from becoming desert of the oasis so as to protect ecosystem. However, the problems that the original plants will be damaged due to the unreasonability in choosing species or the new plants will die due to mismanagement must be solved because the environment of the edge of the desert is very special. Otherwise, they will bring about some negative effect. This paper puts forward my own understanding and thought on these problems. Key words: desert, edge, giving up farming and returning the wood (grass), thought Resume : La region marginale du desert est un secteur de passage entre l’oasis et le desert , la mise en application du retour de la culture au reboisement est une mesure tres efficace pour empecher le mouvement de la dune , la desertification de l’ecologie de l’oasis et pour proteger l’environnement ecologique , mais vu les particularites de l’environnement dans la region marginale du desert , l’ ecologie sera atteinte si les problemes des choix inconvenables des especes dans ce processus , l’imperfectionnement de la gestion, ne sont pas resolus sans retarder Mots-cles : desert , region marginale , retour de la culture au reboisement , reflexion 摘要：沙漠邊緣地帶作為綠洲與沙漠的過度地段，實施退耕還林（草）可以有效的防止沙丘的移動，阻止綠洲生態的進一步沙漠化，保護生態環境，但是沙漠邊緣地帶因其環境的特殊性，在退耕還林（草）中由於物種選擇不合理、原生植被被破壞、管理不善導致初生植被死亡等問題，若不及時解決，則會給生態帶來一定的負面效應。本文針對這一問題提出自己的認識與思考。 關鍵詞：沙漠；邊緣地帶；退耕還林（草）；思考
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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 | 0.001 | 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 | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".