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Record W2019169111 · doi:10.1002/evan.10121

Evolutionary ecology, sexual conflict, and behavioral differentiation among baboon populations

2003· review· en· W2019169111 on OpenAlexaff
S. Peter Henzi, Louise Barrett

Bibliographic record

VenueEvolutionary Anthropology Issues News and Reviews · 2003
Typereview
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsBaboonEcologyBiologyPapio anubisSexual dimorphismSexual selectionGeographyEvolutionary biologyZoology

Abstract

fetched live from OpenAlex

Abstract A central assumption of baboon socio‐ecological models is that all populations have the same capacity to react to different environments. The burden of our argument is that this assumption needs to be reconsidered. Data suggest not only that hamadryas, but chacma as well, differ in interesting ways from the stock baboon model that has been derived, in the main, from earlier work on anubis and cynocephalus. Although environmental factors are behind these differences, much of their influence is a consequence of their effect on restricted ancestral populations, where selection for appropriate responses to the social challenges set by local conditions now constrains the nature of individual responses to contemporary environments. Available genetic evidence suggess a southern African origin for Papio at a time when climatic conditions were certainly no better than they are now and when temperatures, if nothing else, were probably lower. In light of this, a reconstruction of how climate has structured the sexual conflict between males and female charcma, which itself hinges on infanticide, can help explain not only the East African pattern, but also how the apparently anomalous hamadryas pattern has been derived.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.151
GPT teacher head0.454
Teacher spread0.304 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations153
Published2003
Admission routes1
Has abstractyes

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