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ANTIMICROBIAL DEFENSE SHOWS AN ABRUPT EVOLUTIONARY TRANSITION IN THE FUNGUS-GROWING ANTS

2008· article· en· W2120061748 on OpenAlexaff
William O. H. Hughes, Roberta Pagliarini, Henning Bang Madsen, Michiel B. Dijkstra, Jacobus J. Boomsma

Bibliographic record

VenueEvolution · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsMcGill University
FundersSmithsonian Tropical Research InstituteDanmarks GrundforskningsfondFoundation for the National Institutes of Health
KeywordsBiologyFungusMatingHost (biology)Resistance (ecology)ZoologyHymenopteraEcologyEvolutionary biologyBotany

Abstract

fetched live from OpenAlex

Understanding the relative evolutionary importance of parasites to different host taxa is problematic because the expression of disease and resistance are often confounded by factors such as host age and condition. The antibiotic-producing metapleural glands of ants are a potentially useful exception to this rule because they are a key first-line defense that are fixed in size in adults. Here we conduct a comparative analysis of the size of the gland reservoir across the fungus-growing ants (tribe Attini). Most attines have singly mated queens, but in two derived genera, the leaf-cutting ants, the queens are multiply mated, which is hypothesized to have evolved to improve colony-level disease resistance. We found that, relative to body size, the gland reservoirs of most attines are similar in size but that those of the leaf-cutting ants are significantly larger. In contrast, the size of the reservoir did not relate with the evolutionary transition from lower to higher attines and correlated at most only slightly with colony size. The results thus suggest that the relationship between leaf-cutting ants and their parasites is distinctly different from that for other attine ants, in accord with the hypothesis that multiple mating by queens evolved to improve colony-level disease resistance.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.365

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 head0.013
GPT teacher head0.238
Teacher spread0.224 · 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 designBench or experimental
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

Citations36
Published2008
Admission routes1
Has abstractyes

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