α-Pinene concentrations in bark tissue affect intra-specific variation in the susceptibility to vole gnawing of Japanese larch
Bibliographic record
Abstract
During observations of a 46-year-old progeny test site planted with Japanese larch ( Larix kaempferi) in Japan’s Hokkaido region, we observed extensive damage caused by feeding of the gray red-backed vole ( Craseomys rufocanus). In this site, progeny derived from 15 parent clones of L. kaempferi was planted with intercrossed hybrid ( Larix gmelinii var. japonica × L. kaempferi), enabling us to assess genetic contributions to intra-specific variation while accounting for spatial effects. Quantitation using LiDAR and 3D point-cloud data revealed that the genetic characters estimated for the vole-gnawed area varied widely among the parent clones, suggesting that vole susceptibility is a genetically-based trait. Moreover, there was a significant positive relationship between the vole-gnawed area and mortality risk over the last 15 years, suggesting that vole susceptibility of clones is important in mature larch trees as well as in young trees. A significant negative correlation between the vole-gnawed area and the concentrations of α-pinene was detected in the secondary phloem of L. kaempferi, but not in its hybrid. Thus, α-pinene would be a candidate repellent, and the susceptibility to vole gnawing could be genetically improved by breeding approaches for L. kaempferi.
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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 | 0.000 | 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 | 0.000 | 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".