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Record W2178533255 · doi:10.1177/1059712315611733

Evolutionary models for the retention of adult–adult social play in primates: The roles of diet and other factors associated with resource acquisition

2015· article· en· W2178533255 on OpenAlexaff
Brian C. O’Meara, Kerrie Lewis Graham, Sergio M. Pellis, Gordon M. Burghardt

Bibliographic record

VenueAdaptive Behavior · 2015
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsUniversity of Lethbridge
FundersNational Science Foundation
KeywordsBiologyJuvenilePrimatePhylogenetic treeContext (archaeology)Nonhuman primateEcologyPhylogenetic comparative methodsEvolutionary biologyDevelopmental psychologyPsychology

Abstract

fetched live from OpenAlex

What factors in animal life history facilitate or reduce the probability that a species will perform play behavior? While some relationships are known within species and across individuals, it is not obvious that such relationships can be used to explain differences and similarities in amount and type of play across large taxonomic groupings of animals, let alone transitions among them. Primates encompass a relatively large assemblage of species that differ in numerous dietary, habitat, reproductive, and physiological processes. While all juvenile primates engage in social play, far fewer primate species engage in social play as adults. Here, derived from theory and more small-scale comparisons, we explore several biological and behavioral phenomena that differ among nonhuman primates and which may explain differences in the occurrence of adult–adult social play. We used phylogenetic logistic regression to assess the correlation of adult play with various life-history, metabolic and socioecological variables. Although the main contribution of our paper is demonstrating use of phylogenetic methods in the context of play evolution, suggestive but not significant evidence was found that adult sexual and nonsexual social play is influenced by diet, habitat, reproductive, and metabolic factors, sometimes in opposite directions, that we discuss along with needed future analyses involving improved data and interactions among traits.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.085
GPT teacher head0.316
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations14
Published2015
Admission routes1
Has abstractyes

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