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Record W2113753050 · doi:10.1098/rsbl.2013.0621

Differences in group size and the extent of individual participation in group hunting may contribute to differential prey-size use among social spiders

2013· article· en· W2113753050 on OpenAlexaff
Gyan Harwood, Leticia Avilés

Bibliographic record

VenueBiology Letters · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSocialityBiologyPredationEcologyRange (aeronautics)Social groupZoologySocial psychology

Abstract

fetched live from OpenAlex

We have previously shown that the range of prey sizes captured by co-occurring species of group-hunting social spiders correlates positively with their level of sociality. Here, we show that this pattern is probably caused by differences among species in colony size and the extent to which individuals participate in group hunting. We assess levels of participation for each species from the fraction of individuals responding to the struggling prey that partake as attackers and from the extent to which the number of attackers increases with colony size. Of two species that form equally large colonies, the one that captures on average larger prey engaged as attackers a significantly larger fraction of individuals that responded to struggling prey and also increased its number of attackers in larger colonies when presented with large prey items. Surprisingly, a third co-occurring species previously found to capture smaller insects than the other two exhibited the highest levels of participation. This species, however, typically forms small single-family colonies, thereby being limited in the size of insects it can capture. It is thus a combination of colony size and the extent of individual participation (or cooperation) that probably determines patterns of resource use in this community of co-occurring social predators.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.389

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 head0.015
GPT teacher head0.252
Teacher spread0.238 · 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

Citations22
Published2013
Admission routes1
Has abstractyes

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