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Fitness‐related traits in a parasitoid fly are mediated by effects of plants on its host

2008· article· en· W2005376956 on OpenAlexafffund
Valérie Caron, Judith H. Myers, David R. Gillespie

Bibliographic record

VenueJournal of Applied Entomology · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyGeneralist and specialist speciesParasitoidBiological pest controlHost (biology)HerbivoreLarvaTrichoplusiaPupaBotanyHorticultureEcologyHabitatNoctuidae

Abstract

fetched live from OpenAlex

Abstract Plants can affect parasitoids directly, by reducing or enhancing their ability to locate hosts, or indirectly by affecting the fitness of herbivores and thus of parasitoids. Tritrophic interactions between three host plants (cucumber, tomato, sweet pepper), a polyphagous herbivore Trichoplusia ni and a generalist parasitoid Compsilura concinnata were assessed. Plants had a strong effect on T. ni larval survival, as well as on C. concinnata fitness‐related traits: cucumber‐fed hosts yielded parasitoids with shorter larval development time and females had heavier pupal weights than parasitoids from host larvae that were fed tomato. Furthermore, C. concinnata was more efficient at finding cucumber‐fed than tomato‐fed T. ni . These results suggest that C. concinnata has different efficiency and potential as a biocontrol agent on the different crops. This highlights the importance of assessing tritrophic interactions in systems where an inundative biological control agent may be released against generalist targets on more than one crop plant.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 head0.010
GPT teacher head0.215
Teacher spread0.205 · 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

Citations22
Published2008
Admission routes2
Has abstractyes

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