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Record W2031225922 · doi:10.1139/z03-070

Rapid female multiple mating in red flour beetles (<i>Tribolium castaneum</i>)

2003· article· en· W2031225922 on OpenAlexvenueno aff
Aditi Pai, Guiyun Yan

Bibliographic record

VenueCanadian Journal of Zoology · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsBiologyMatingRed flour beetleFertilityAntagonistic CoevolutionOffspringZoologyFecunditySexual conflictEcologyLarvaPregnancyDemographyPopulationGenetics

Abstract

fetched live from OpenAlex

Many female insects mate with multiple males within a single fertile period despite costs such as expenditure of energy and time and contraction of sexually transmitted diseases. In the red flour beetle, Tribolium castaneum, females remate with different males within minutes of the first copulation. If rapid multiple mating is adaptive then multiply mated females should have higher fitness than singly mated females. In this study, we determined the remating frequency of female beetles, characterized female mating behavior, and examined the fitness consequences of female multiple mating. We found that female T. castaneum mated, on average, with 4–6 nonvirgin males within a 1-h observation period. The number of males present in a mating arena did not significantly affect copulation frequency or the intermating interval. However, number of males present significantly affected the length of a single copula as a result of disturbance by rival males when more males were present. Female mating with multiple males in 24 h did not significantly improve egg production, F 1 -adult production, egg-to-adult viability, fertility retention, and female survivorship. Thus, multiple mating did not enhance long-term female fitness. Polyandrous mating behavior may have evolved through other mechanisms such as fertility assurance and increased offspring genetic diversity or fitness.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.037
GPT teacher head0.233
Teacher spread0.196 · 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.

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

Citations37
Published2003
Admission routes1
Has abstractyes

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