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Record W2085372723 · doi:10.1371/journal.pone.0028612

Do Singing Rock Hyraxes Exploit Conspecific Calls to Gain Attention?

2011· article· en· W2085372723 on OpenAlexaff
Amiyaal Ilany, Adi Barocas, Lee Koren, Michael Kam, Eli Geffen

Bibliographic record

VenuePLoS ONE · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSingingHyraxStimulus (psychology)CommunicationPsychologyAnimal communicationAudiologyBiologyCognitive psychologyEcologyAcousticsPhysicsMedicine

Abstract

fetched live from OpenAlex

Signal detection theory predicts that signals directed at distant or busy receivers in noisy backgrounds will begin with an alert component, in order to draw attention. Instead of an alert component, however, animals could get the same effect by using an external stimulus. Here we combined observations of free-living rock hyraxes (Procavia capensis) with playback experiments to elucidate the circumstances under which males begin singing. We show that males sing following hyrax pup screams, which elicit a strong response from hyraxes within hearing distance, which are potential receivers. We hypothesize that singers enhance their singing display by exploiting the rarely emitted pup screams. To our knowledge, our findings are the first indication that animals may enhance signal reception by exploiting conspecifics' signals and the differential attention to these signals. We suggest that the utilization of external stimuli by signalers may be widespread, as an adaptive strategy for communication in complex environments.

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 score0.019
Threshold uncertainty score0.403

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 head0.136
GPT teacher head0.277
Teacher spread0.140 · 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

Citations20
Published2011
Admission routes1
Has abstractyes

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