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Information on Resource Quality Mediates Aggression between Male Madagascar Hissing Cockroaches,<i>Gromphadorhina portentosa</i>(Dictyoptera: Blaberidae)

2005· article· en· W2010058227 on OpenAlexafffund
Patrick A. Guerra, Andrew C. Mason

Bibliographic record

VenueEthology · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAggressionDominance (genetics)Dominance hierarchyDictyopteraCockroachZoologyBiologyContext (archaeology)PolygynyPsychologyEcologyDemographyDevelopmental psychologyPopulation

Abstract

fetched live from OpenAlex

Abstract Male Madagascar hissing cockroaches, Gromphadorhina portentosa Schaum (Dictyoptera: Blaberidae) have a well‐defined dominance hierarchy that has been assumed to explain the outcome of most competitive interactions. We studied whether males of this species would alter their level of aggression towards unfamiliar rivals as a function of changing resource availability and value – two factors that are key to aggression levels in non‐hierarchical species. We quantified male aggression as three variables (aggressive state – behaviours measured by their duration; aggressive act – behaviours measured by their frequency of occurrence; aggressive latency – the latency to first aggressive behaviour, either state or act) and tested for any context‐specific variation within each by manipulating both territorial status (males were either residents or intruders) and access to mates (female present or absent). Both the presence of a female and territorial status affected male aggression towards rivals as measured by duration of aggressive state. Highest levels of aggression were displayed by residents when a female was present. These results show that inter‐male aggression in G. portentosa is tuned to the immediate expected payoff from fighting, and not exclusively aimed at establishing dominance relationships (which can affect future payoffs).

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.310

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 head0.064
GPT teacher head0.264
Teacher spread0.200 · 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

Citations23
Published2005
Admission routes2
Has abstractyes

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