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Unequal distribution of local mating opportunities in an egg parasitoid

2007· article· en· W1992623018 on OpenAlexafffund
Véronique Martel, Guy Boivin

Bibliographic record

VenueEcological Entomology · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsMcGill UniversityAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsBiologyBiological dispersalParasitoidMatingSpermSperm competitionHymenopteraEcologyZoologyTrichogrammatidaeCompetition (biology)DemographyBotanyPopulation

Abstract

fetched live from OpenAlex

Abstract 1. The Local Mate Competition (LMC) model predicts that, in gregarious and quasi‐gregarious species, a lone female exploiting a host patch will lay only the minimal number of sons necessary to inseminate all daughters, but as the number of foundresses increases, the proportion of sons deposited by these females also increases. 2. For off‐patch mating to occur, non‐sperm‐depleted males must leave the patch and find virgin females. 3. To investigate the distribution of matings among males, the sperm stock at dispersal and the time of dispersal were quantified for male Trichogramma turkestanica (Hymenoptera: Trichogrammatidae). 4. Matings were not distributed equally among males: some successful males acquired more matings than others. Because of this, a high variability in the sperm stock at dispersal was observed. While few males dispersed almost empty or almost full, the majority of males dispersed with enough sperm to be able to mate with females outside the emergence patch. 5. The mating capacity was thus higher than necessary for local mating and could be explained by an unequal distribution of mating opportunities and the occurrence of off‐patch mating.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.104
GPT teacher head0.278
Teacher spread0.173 · 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 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

Citations19
Published2007
Admission routes2
Has abstractyes

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