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Record W4286492042 · doi:10.1139/cjz-2022-0043

Triggers and consequences of wolf (<i>Canis lupus</i>) howling in Yellowstone National Park and connection to communication theory

2022· article· en· W4286492042 on OpenAlexaffvenue
John B. Theberge, Mary T. Theberge

Bibliographic record

VenueCanadian Journal of Zoology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCanisVocal communicationSocialitySocial animalBiologyAnimal communicationCommunicationFlexibility (engineering)EcologyPair bondPsychologyCognitive psychology

Abstract

fetched live from OpenAlex

Animal vocal communication is rife with concepts that, while important, are difficult to evaluate in nature. Particularly interesting is their application to large social mammalian carnivores characterized by year-long, loud vocalization. Here, we quantified triggers and consequences of 504 wolf ( Canis lupus Linnaeus, 1758) howl events in Yellowstone National Park observed across 16 years. We related our results to two general theories of animal communication: that vocalization is more about communicating emotional/motivational states than a purposeful transfer of detailed information and that flexibility in use of long-distance vocalizations has been important to overall behavioural plasticity and advanced sociality in non-human primates and large social carnivores. In our study, half the howl events were triggered by 12 different environmental or social situations, most of which generated levels of anxiety. The remainder were non-triggered, apparently motivated internally but in contexts that reflected basic adaptive drives such as bonding and pack coordination. Approximately half of all howl events elicited either a change in sender activity or responding howls or travel from distant wolves, which we quantified. Wolf howling was inconsistent (low percentage of occurrence) in most behavioural contexts, hence demonstrating flexibility and social discrimination in its use. Thus, both theories were strongly supported.

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 score0.571
Threshold uncertainty score0.615

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 science0.0000.000
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 head0.018
GPT teacher head0.262
Teacher spread0.244 · 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

Citations6
Published2022
Admission routes2
Has abstractyes

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