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Record W2139079256 · doi:10.2980/21-1-3682

The role of birds in the acacia—ant interaction: New insights from nest predation

2014· article· en· W2139079256 on OpenAlexvenueno aff
Octavio Rojas‐Soto, Ian MacGregor‐Fors, Cecilia Díaz‐Castelazo, Ángel A. Molina-García, César Maldonado-Hernández

Bibliographic record

VenueEcoscience · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsAcaciaNest (protein structural motif)PredationBiologyMyrmecophyteMutualism (biology)ANTEcologyAnt colonyPredatorZoology

Abstract

fetched live from OpenAlex

Abstract: The association of the swollen-thorn acacia (Acacia cornigera) and ants is an example of defensive mutualism. It has been shown that some bird species prefer to nest in myrmecophyte acacias, suggesting that their nests are protected from predators by the associated ants. Based on previous knowledge regarding the existence of extended benefits for birds in the acacia—ant interaction, the role of the rufous-naped wren was analyzed within the ant—acacia system. Nest predation was assessed taking into account tree species with and without myrmecophytic interactions, tree cover and height, the presence and abundance of ants, predator type, and the distance between each nest and the closest myrmecophyte acacia. The probability of survivorship of artificial nests using a known fate analysis was calculated. The results showed non-significant differences in the probability of survivorship regardless of the presence and density of myrmecophyte acacias, tree cover and height, the presence and abundance of ants, or predator type. Interestingly, the highest degree of predation in the artificial nests was related to the rufous-naped wren. These results suggest that the acacia—ant—bird interaction is more complex than previously perceived.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.999

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 head0.027
GPT teacher head0.207
Teacher spread0.180 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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