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Record W4404468736 · doi:10.1101/2024.11.18.623889

Self-organized acoustic behavior in bats arises from simple rules

2024· preprint· en· W4404468736 on OpenAlexaff
Kazuma Hase, Seiya Oka, Noriyoshi Senoo, Hiraku Nishimori, Masashi Shiraishi, Ken Yoda, Kohta I. Kobayasi, Shizuko Hiryu

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicScientific Research and Discoveries
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSimple (philosophy)Computer scienceAcousticsPhysicsEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract Although self-organized behavior has been extensively studied in the movement of group-behaving animals, such as fish or birds, far less attention has been paid to vocal behavior in animal groups, especially in mammals. Here, by testing the vocal response of echolocating bats ( Miniopterus fuliginosus ) to the playback of jamming stimuli in the lab, we discovered a mathematical model that can well describe vocal frequency control by bats in response to jamming stimuli mimicking echolocation sounds emitted in a group of bats. We then extended the model to a group of flying bats and observed frequency-adjusting behavior by which the frequency differences for the group increased overall, similar to a previous observation on group-flying bats. Further, we showed the frequency-adjusting behavior led to less potential misdetections by echolocation in a group. Our findings suggest this frequency-adjusting behavior is a self-organized vocal behavior that mitigates conflicts within a group, one achieved via simple behavioral rules, as in other types of collective animal behavior.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
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 score0.220
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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