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Record W2055844707 · doi:10.1111/nph.12690

Current issues in the evolutionary ecology of ant–plant symbioses

2014· review· en· W2055844707 on OpenAlexaff
Veronika Mayer, Megan E. Frederickson, Doyle McKey, Rumsaïs Blatrix

Bibliographic record

VenueNew Phytologist · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMutualism (biology)EcologyMyrmecophyteSymbiosisBiologyHerbivoreEvolutionary ecologyANTAnt colonyCoevolutionHost (biology)NectarComputer science

Abstract

fetched live from OpenAlex

Ant-plant symbioses involve plants that provide hollow structures specialized for housing ants and often food to ants. In return, the inhabiting ants protect plants against herbivores and sometimes provide them with nutrients. Here, we review recent advances in ant-plant symbioses, focusing on three areas. First, the nutritional ecology of plant-ants, which is based not only on plant-derived food rewards, but also on inputs from other symbiotic partners, in particular fungi and possibly bacteria. Food and protection are the most important 'currencies' exchanged between partners and they drive the nature and evolution of the relationships. Secondly, studies of conflict and cooperation in ant-plant symbioses have contributed key insights into the evolution and maintenance of mutualism, particularly how partner-mediated feedbacks affect the specificity and stability of mutualisms. There is little evidence that mutualistic ants or plants are under selection to cheat, but the costs and benefits of ant-plant interactions do vary with environmental factors, making them vulnerable to natural or anthropogenic environmental change. Thus, thirdly, ant-plant symbioses should be considered good models for investigating the effects of global change on the outcome of mutualistic interactions.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.035
GPT teacher head0.342
Teacher spread0.307 · 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

Citations129
Published2014
Admission routes1
Has abstractyes

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