Current and Future Potential Risk of Establishment of Grapholita molesta (Lepidoptera: Tortricidae) in Washington State
Bibliographic record
Abstract
The oriental fruit moth, Grapholita molesta (Busck) (Lepidoptera: Tortricidae), is a primary pest of stone fruits that cause significant economic damage. Larvae, which enter the host plant through shoot tips, damage shoots, and ripe fruits. Native to Asia, this pest now occurs in many fruit-growing countries, including the United States and Canada. Though the pest was previously reported from many states within the United States, its current distribution and the environmental variables that influence its distribution are not properly identified. The objectives of this study were to 1) identify the environmental factors associated with G. molesta current distribution, 2) predict the current distribution of G. molesta in Washington State (WA) using Maxent and Climex models, 3) identify those areas within WA best suited for establishment of pest free zones, areas of low pest prevalence, and pest free production areas, and 4) identify regions most at risk for further expansion of G. molesta populations as a function of climate change. The current models predicted a small portion of central WA is suitable to support G. molesta, which is consistent with observed distributions. However, climate change models predict that more areas will become suitable for the pest. These results indicate that action should be taken to monitor and reduce current populations of G. molesta to stem its potential expansion into the major commercial tree fruit production areas in the state.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".