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Record W2592769671 · doi:10.1093/jipm/pmw019

Biology and Management of the Fall Webworm, Hyphantria cunea (Lepidoptera: Erebidae)

2016· article· en· W2592769671 on OpenAlexaboutno aff
Timothy D. Schowalter, D. R. Ring

Bibliographic record

VenueJournal of Integrated Pest Management · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsnot available
FundersU.S. Forest Service
KeywordsHyphantriaBiologyLepidoptera genitaliaErebidaeEcologyPredationRange (aeronautics)

Abstract

fetched live from OpenAlex

The fall webworm, Hyphantria cunea (Drury) (Lepidoptera: Erebidae), is a widespread defoliator that is native throughout the continental United States, as well as southern Canada and northern Mexico. It has been introduced accidentally into many parts of Europe and Asia. Larvae have been recorded from > 400 species of forest and shade trees, primarily hardwoods, but also several conifer species in the southern United States. This species is of minor importance in forests, but can cause serious losses in pecan and fruit tree orchards and is a major nuisance in urban parks and homelots where it often completely defoliates ornamental and shade trees. Fall webworm larvae construct conspicuous webs that start at the ends of branches and expand as the larvae grow to incorporate multiple branches. Foliage within webs is completely consumed. Two color races occur throughout the range of this moth, but pure white adults and black-headed larvae predominate in northern regions, whereas spotted adults and red-headed larvae predominate in southern regions. Populations of fall webworm are regulated naturally in its native range by host quality and abundance and by at least 50 species of dipteran and hymenopteran parasitoids and 36 species of predators and parasites. Physical removal, biocontrol, and insecticides are available for management of this moth.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations75
Published2016
Admission routes1
Has abstractyes

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