Species association in Xanthoceras sorbifolium Bunge communities and selection for agroforestry establishment
Bibliographic record
Abstract
We embraced the “learning from nature and back to nature” paradigm to develop viable agroforestry scenarios through studying species association in 12 wild yellowhorn ( Xanthoceras sorbifolium : a Chinese endemic oil woody plants) communities. We identified 18 species combinations for their suitability as agroforestry mixes where positive associations were detected and thus economic benefits are anticipated. In each wild yellowhorn community, we use nonmetric multidimensional scaling ordination to assess community structure and composition, and the climatic variables that most likely influenced existing species distributions. Next, pairwise and multiple species associations were evaluated using several multiple species association indices (e.g., χ 2 , Jaccard, Ochiai, Dice). Generally, all species association indices were in agreement and were helpful in identifying several high valued medicinal species that showed positive and significant associations with yellowhorn. Finally, we proposed several agroforestry species mixes suitable for yellowhorn.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".