MétaCan
Menu
Back to cohort
Record W2160480000 · doi:10.1093/jhered/esj001

Inbreeding Ancestors: The Role of Sibmating in the Social Evolution of Gall Thrips

2006· article· en· W2160480000 on OpenAlexaff
Michael McLeish, Tom Chapman, Bernard J. Crespi

Bibliographic record

VenueJournal of Heredity · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBiologyThripsGallInbreedingEvolutionary biologyZoologyEcologyDemographyBotanySociologyPopulation

Abstract

fetched live from OpenAlex

We used microsatellite data to estimate levels of inbreeding in four species of solitary gall thrips that are in the same clade as the six species with soldier castes. Three of the four species were highly inbred (Fis 0.54-0.68), and the other apparently mated randomly (Fis near zero). These estimates, combined with previous data from species with soldiers, suggest that inbreeding is a pervasive life-history feature of the gall-inducing thrips on Australian Acacia. Mapping of inbreeding estimates onto the phylogeny of the gall inducers showed that the ancestral lineage that gave rise to soldiers was apparently highly inbred, and therefore, inbreeding could have played a role in the origin of sociality within this group. Moreover, there was a trend from high levels of inbreeding at the origin of soldiers to low levels in the most derived species with soldiers, which exhibits the highest levels of reproductive division of labor and soldier altruism. These patterns are consistent with considerations from population genetics, which show that the likelihood of the origin of soldier altruism is higher in inbreeding populations but that, once soldiers have evolved, a reduction in inbreeding levels may facilitate the evolution of enhanced division of labor and reproductive skew.

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 score0.481
Threshold uncertainty score0.102

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 head0.011
GPT teacher head0.255
Teacher spread0.245 · 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

Citations24
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of HereditySame topicInsect and Arachnid Ecology and BehaviorFrench-language works237,207