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Record W2092396212 · doi:10.1603/en10237

Early Detection of Prospective Mates by Males of the Parasitoid Wasp <I>Pimpla disparis</I> Viereck (Hymenoptera: Ichneumonidae)

2011· article· en· W2092396212 on OpenAlexaff
Adela Danci, Cesar Inducil, Paul W. Schaefer, Gerhard Gries

Bibliographic record

VenueEnvironmental Entomology · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsIchneumonidaeParasitoidBiologyPupaHymenopteraHost (biology)Lymantria disparZoologyGalleria mellonellaBraconidaeParasitismParasitoid waspPheromoneMatingLarvaEcology

Abstract

fetched live from OpenAlex

In some insect species, the presence of a mate at the time of eclosion appears to facilitate rapid mating, with positive fitness consequences for one or both mates. Field observations that males of the hymenopteran parasitoid Pimpla disparis Viereck aggregated on a gypsy moth, Lymantria dispar (L.), host pupa before the emergence of a female led us to hypothesize that these males responded to chemical cues associated with parasitized host pupae. Results of laboratory experiments with wax moth, Galleria mellonella (L.), host pupae suggest that female P. disparis chemically mark the host pupae they have parasitized and that males discern between such pupae and those not parasitized. As males continue to recognize parasitized host pupae throughout the development of the parasitoid, they could exploit not only the females' marker pheromone but possibly also semiochemical, visual, or vibratory cues from the developing parasitoid inside the host pupa, the decaying host, or both. Irrespective, these cues could help males locate parasitized host pupae and time the emergence of a prospective mate.

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 score0.002
Threshold uncertainty score0.007

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)0.0020.001

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 head0.176
Teacher spread0.170 · 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

Citations10
Published2011
Admission routes1
Has abstractyes

Explore more

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