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Record W2790859798 · doi:10.1093/ee/nvx203

Current and Future Potential Risk of Establishment of Grapholita molesta (Lepidoptera: Tortricidae) in Washington State

2017· article· en· W2790859798 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnvironmental Entomology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pheromone Research and Control
Canadian institutionsnot available
FundersWashington State Department of AgricultureWashington Tree Fruit Research CommissionColorado State UniversityU.S. Department of Agriculture
KeywordsTortricidaePEST analysisBiologyLepidoptera genitaliaEcologyIntegrated pest managementAgronomyBotany

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.215
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it