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Record W2101809669 · doi:10.1093/beheco/arq161

The relative importance of RHP and resource quality in contests with ownership asymmetries

2010· article· en· W2101809669 on OpenAlexaff
Michael M. Kasumovic, Andrew C. Mason, Maydianne C. B. Andrade, Damian O. Elias

Bibliographic record

VenueBehavioral Ecology · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsCONTESTBiologyResource (disambiguation)Reproductive successAttritionQuality (philosophy)Affect (linguistics)DemographyPsychologyCommunication

Abstract

fetched live from OpenAlex

Ownership asymmetries lead to owners (residents) having substantial contest advantages over intruders, and this may overwhelm the fighting advantage of large body size. Why such an ownership advantage occurs, however, is not clear and requires further investigation. Here, we use a jumping spider, Phidippus clarus, to examine the role of ownership asymmetries and resource quality in determining contest outcomes and assessment strategies of both intruders and residents. Resident male P. clarus cohabit with and defend virgin females where reproductive potential increases with body size. Here, we show that ownership plays a significant role in contest outcomes, despite the previously demonstrated importance of body size when males encounter each other in the absence of a female. Owners have a substantial advantage over intruders with residency being more important than body size in determining contest outcomes. Intruders gave up more quickly when owners were larger, suggesting that owners follow a partial mutual assessment strategy. In contrast, contests won by intruders were “wars of attrition” where owners fought until resources were depleted as they were governed by the resource holding potential of the resident (loser). Finally, female size (reproductive potential) did not alter contest outcomes; however, it did affect how quickly contests were escalated. We highlight the importance of understanding the life history and reproductive biology along with the behavior and ecology of the species under study to truly understand the traits associated with fitness in contests.

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 score0.064
Threshold uncertainty score0.965

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 head0.040
GPT teacher head0.293
Teacher spread0.253 · 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

Citations39
Published2010
Admission routes1
Has abstractyes

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