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Record W2095302904 · doi:10.4039/n03-024

Influence of wing loading on Colorado potato beetle flight

2004· article· en· W2095302904 on OpenAlexafffund
Chris J.K. MacQuarrie, Gilles Boiteau, Dan T. Quiring

Bibliographic record

VenueThe Canadian Entomologist · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of New Brunswick
FundersAgriculture and Agri-Food Canada
KeywordsLeptinotarsaColorado potato beetleWingPopulationBiologyBacillus thuringiensisPEST analysisRange (aeronautics)InsectBotanyHorticultureAgronomyAnimal science

Abstract

fetched live from OpenAlex

Abstract Flight of overwintered and summer population Colorado potato beetles, Leptinotarsa decemlineata Say (Coleoptera: Chrysomelidae), with a range of wing loadings was measured following exposure to different quality diets. Beetles fed a diet of insect-resistant foliage expressing Bacillus thuringiensis tenebrioniz toxins, beetles that did not feed but consumed water, and those that were starved without access to water exhibited a lower range of wing loadings than those fed conventional foliage, but there was no corresponding increase in flight frequency. Exposing potato beetles to poor food or no food resulted in a wing-loading range of 50–140 mg/cm 2 compared with a range of 80–200 mg/cm 2 for beetles fed conventional foliage. No flight was observed when wing loadings were less than 80 mg/cm 2 of wing surface, presumably because of other physiological processes associated with poor nutrition and not because of wing loading per se. Overwintered and summer population beetles fed a diet of conventional potato foliage did not take off when wing loading exceeded 150 mg/cm 2 of supporting wing surface. Similar trade-offs between flight capacity and consumption of large meals may exist for other insects.

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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.782
Threshold uncertainty score0.568

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 head0.014
GPT teacher head0.215
Teacher spread0.202 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations6
Published2004
Admission routes2
Has abstractyes

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