Mass attack by the ambrosia beetle<i>Platypus quercivorus</i>occurs in single trees and in groups of trees
Bibliographic record
Abstract
Bark and ambrosia beetles sometimes kill trees by attacking them en masse; however, their attack is not necessarily successful. Less than half of the fagaceous trees attacked by the ambrosia beetle Platypus quercivorus (Murayama) die, and the factors affecting this mortality are still unknown. To examine this issue, the survival of all stems of fagaceous trees attacked by the ambrosia beetle was investigated in a secondary forest from 2008 to 2010. In an area of 93 ha, 2130 stems (1278 genets) of fagaceous trees were attacked by P. quercivorus during the study period, and 813 of these stems died. A generalized additive mixed model was constructed to predict the probability of mortality of the attacked stems. A best-fit model showed that the probability of mortality was higher in Quercus crispula Blume than in Castanea crenata Sieb. & Zucc. A positive correlation was determined between the density of the attacked trees and the probability of mortality, suggesting that mass attack of P. quercivorus occurs not only on individual trees, but also on groups of trees. Assuming that trees attacked earlier in the season have a higher probability of mortality, the observed negative effects of altitude suggest that P. quercivorus initially seeks hosts at lower elevations.
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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 | 0.001 | 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) | 0.001 | 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".