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Record W4387517805 · doi:10.1038/s42003-023-05392-y

Widow spiders alter web architecture and attractiveness in response to same-sex competition for prey and mates, and predation risk

2023· article· en· W4387517805 on OpenAlexafffund
Andreas Fischer, Yasasi Fernando, April Preston, Sarah Moniz-de-Sa, Gerhard Gries

Bibliographic record

VenueCommunications Biology · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPredationAttractivenessCompetition (biology)BiologyZoologyEcologyPsychology

Abstract

fetched live from OpenAlex

Female-female competition in animals has rarely been studied. Responses of females that compete context-dependently for mates and prey, and seek safety from predators, are ideally studied with web-building spiders. Cobwebs possess unique sections for prey capture and safety, which can be quantified. We worked with Steaoda grossa females because their pheromone is known, and adjustments in response to mate competition could be measured. Females exposed to synthetic sex pheromone adjusted their webs, indicating a perception of intra-sexual competition via their sex pheromone. When females sequentially built their webs in settings of low and high intra-sexual competition, they adjusted their webs to increase prey capture and lower predation risk. In settings with strong mate competition, females deposited more contact pheromone components on their webs and accelerated their breakdown to mate-attractant pheromone components, essentially increasing their webs' attractiveness. We show that females respond to sexual, social and natural selection pressures originating from intra-sexual competition.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.170

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.046
GPT teacher head0.309
Teacher spread0.262 · 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

Citations8
Published2023
Admission routes2
Has abstractyes

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