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Is dump material an effective small-scale deterrent to herbivory by leaf-cutting ants?

2003· article· en· W2543165911 on OpenAlexvenueno aff
Alejandro G. Farji‐Brener, Yamila Sasal

Bibliographic record

VenueEcoscience · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsHerbivoreScale (ratio)BiologyEcologyGeography

Abstract

fetched live from OpenAlex

It has been suggested that refuse dumps from leaf-cutting ant nests work as a herbivory deterrent for leaf-cutting ants because dumps harbour micro-organisms that are dangerous to ants and their symbiotic fungus. However, this deterrent effect was tested for the narrowly distributed Atta colombica only during a five-day period. We experimentally tested the refuse-deterrent effect for a longer period using the broadly distributed Acromyrmex lobicornis. Although refuse mounds around plants significantly delayed the initiation of attack by A. lobicornis, almost all plants (~90%), surrounded or not by refuse, were killed by leaf cutters in a few weeks. Therefore, the refuse-deterrent technique may not be useful as a widespread method of biological control for leaf-cutting ants. The refuse showed an improved deterrent effect when both the dump material and the leaf-cutting ant came from the same colony, suggesting that the pathogens for both ant and fungus found in refuse dumps might be nest-specific.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.463

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 head0.009
GPT teacher head0.258
Teacher spread0.248 · 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

Citations30
Published2003
Admission routes1
Has abstractyes

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