Evaluation of soil and water conservation capacities for plantations on the Simian Mountains of China
Bibliographic record
Abstract
Eighteen indices were selected to evaluate soil and water conservation capacities of four different mixtures of plantations using the Ideal Point Method. Results indicate that a broadleaf plantation of robur (Lithocarpus glabra) and Chinese guger tree (Schima superba) had the best conservation capacity, a mixed broadleaf plantation of sweetgum (Liquidambar formosana), Chinese gugertree and camphor tree (Cinnamomum camphora) was ranked second. A mixed broadleaf–conifer plantation of Chinese fir (Cunninghamia lanceolata), Masson pine (Pinus massoniana) and Chinese gugertree ranked third with a mixed coniferous plantation (Chinese fir and Masson pine) fourth. Under similar climates and topographical conditions, broadleaf plantations have better soil and water conservation capacities than conifer plantations. Sensitivity analysis showed that litter amounts and soil properties are the most important indicators of soil and water conservation capacities of plantations. Suitable measures such as deep tillage should be used to improve soil aggregation in different plantations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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 source (direct Gemma or distilled Codex), 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".