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Patch time allocation in male parasitoids

2008· article· en· W2157396700 on OpenAlexaff
Véronique Martel, Éric Wajnberg, Guy Boivin

Bibliographic record

VenueEcological Entomology · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyParasitoidSex allocationTrichogrammaTime allocationHost (biology)HymenopteraBraconidaeEcology

Abstract

fetched live from OpenAlex

Abstract 1. Patch time allocation has been mostly studied in female parasitoids exploiting patches of hosts. Different parameters such as oviposition, host encounters, patch quality, etc. have been repeatedly shown to modify the time females invest on hosts. 2. Male parasitoids are expected to maximise their lifetime fitness by maximising the number of females inseminated during their life. Because they can be sperm and/or time limited, they should optimise their time allocation on emergence patches. 3. Patch time allocation thus appears to be an important question for both male and female parasitoids. 4. In this study, we determined the parameters used by males of the egg parasitoid Trichogramma turkestanica to decide when to leave the emergence patch. Among the different patch‐leaving parameters tested, only contacts with parasitised hosts and presence of virgin females significantly influenced the patch‐leaving tendency. 5. Our results suggest that males express behaviours that could enable them to optimise their patch exploitation time, as females do, but using different strategies.

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 score0.008

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)0.0020.000

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 head0.222
Teacher spread0.208 · 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

Citations11
Published2008
Admission routes1
Has abstractyes

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