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Record W2344649502 · doi:10.1676/1559-4491-128.1.180

Lethal Agonistic Behavior between Two Male Magellanic Woodpeckers <i>Campephilus magellanicus</i> Observed in the Cape Horn Area

2016· article· en· W2344649502 on OpenAlexaff
Gerardo E. Soto, Pablo M. Vergara, Ashley Smiley, Marlene E Lizama, Darío Moreira‐Arce, Rodrigo A. Vásquez

Bibliographic record

VenueThe Wilson Journal of Ornithology · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAgonistic behaviourWoodpeckerZoologyEcologyBiologyAggressionPsychologyDevelopmental psychologyHabitat

Abstract

fetched live from OpenAlex

Agonistic behavior in woodpeckers has been described for a wide range of species, although previous studies have not reported aggressive encounters resulting in the death of adults. In this study, we provide the first evidence of lethal agonistic behavior between two male Magellanic Woodpeckers (Campephilus magellanicus) inhabiting Patagonia. This species is commonly regarded as the largest extant Campephilus woodpecker. The agonistic encounter was video recorded within the core territory of the dead individual and his mate, a previously banded and monitored pair, as part of a monitoring research on this species carried out during the last 2 years. A week after the fight, we recorded a non-banded young male Magellanic Woodpecker accompanying the dead individual’s mate. This young male Magellanic Woodpecker is potentially the offspring of the former pair or perhaps a new mate replacing the dead individual. From this observation, we deduced that the previously occupied territory of the dead individual, as well as its breeding role, was subjected to reallocation by competing adjacent woodpecker families. This mortality event offers novel insight into the behavior of Magellanic Woodpeckers and suggests that lethal agonistic behavior likely could contribute to territory plasticity and family structure in this species.

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 score0.552
Threshold uncertainty score0.533

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 science0.0010.000
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 head0.058
GPT teacher head0.259
Teacher spread0.201 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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