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Monotony and the Information Content of Richardson's Ground Squirrel (<i>Spermophilus richardsonii</i>) Repeated calls: Tonic Communication or Signal Certainty?

2004· article· en· W2000632329 on OpenAlexaff
Jennifer L. Sloan, James F. Hare

Bibliographic record

VenueEthology · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAlarm signalVigilance (psychology)PsychologyTonic (physiology)ALARMAlertnessCommunicationAnimal communicationCertaintyAudiologyCognitive psychologyMathematicsNeuroscience

Abstract

fetched live from OpenAlex

Abstract The repetition of elements within an alarm signal is commonly thought to ensure that receivers have detected that signal, or to promote residual vigilance in light of the dangerous circumstances prompting the signal's initial production (tonic communication). Beyond alerting others and maintaining that state of alertness, however, repetitive signal elements may be parsed so as to encode information about the nature of potential threats. To determine how call length and variation in intersyllable latency might prove informative in the repetitive alarm vocalizations of Richardson's ground squirrels ( Spermophilus richardsonii ), we conducted a field‐based playback experiment quantifying antipredator responses to manipulated alarm calls. Free‐living juvenile squirrels were exposed to playbacks of 12 syllable (long) and six syllable (short) calls with a constant (monotonous) or changing (variable) call rate. The length of calls had no significant effect on the behaviour of call recipients during and immediately after call production; however, call recipients showed greater vigilance after the playback of monotonous calls than after variable calls. The absence of a call length effect is not consistent with tonic communication in the strict sense; rather, enhanced responsiveness to monotonous relative to variable calls suggests that multiple syllables, and the emergent patterns of intersyllable latency, communicate information about response urgency or the distance to a predatory threat. Only monotonous calls convey those aspects with any certainty on the part of the signaller and hence are selectively attended to by receivers.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.358

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 studies0.0000.001
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 head0.032
GPT teacher head0.276
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 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

Citations27
Published2004
Admission routes1
Has abstractyes

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