Economic Effects of Mitigating Apple Maggot Spread
Bibliographic record
Abstract
Apple maggot is an economically important apple pest that is native to the East Coast of North America, including Canada and the United States. Introduced to the West Coast of the United States in 1979, the pest is spreading rapidly in the region, threatening the major apple production area of Washington State, as well as British Columbia. A dynamic simulation model for perennial fruit production is developed to study the potential economic impact of a pest species, such as apple maggot. The model is designed to provide essential information, including the intertemporal distribution of welfare, to aid the design of effective and efficient policy response to pest outbreaks. This model is used to simulate the economic impact of apple maggot spread in Washington State on apple price, trade flows, and welfare changes. La mouche de la pomme est un ravageur originaire de la côte Est de l'Amérique du Nord (canadienne et étatsunienne) qui cause des pertes économiques considérables. Ce ravageur, qui s'est introduit sur la côte Ouest des États‐Unis en 1979, se propage rapidement et menace les principales zones de production de pomme de l'État de Washington et de la Colombie‐Britannique. Nous avons élaboré un modèle de simulation dynamique pour la production pluriannuelle de fruits afin d'étudier l'incidence économique potentielle d'espèces ravageuses telles que la mouche de la pomme. Le modèle a été conçu pour fournir de l'information essentielle, dont la distribution du bien‐être intertemporel, en vue de contribuer à l'élaboration d'une réaction politique efficace de lutte contre les pullulations de ravageurs. Ce modèle est utilisé pour simuler l'incidence économique de la propagation de la mouche de la pomme dans l'État de Washington sur le prix des pommes, le flux des échanges commerciaux et les changements touchant le bien‐être.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".