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Record W2095989382 · doi:10.1242/bio.201511908

Echolocation in the bat, <i>Rhinolophus capensis</i>: the influence of clutter, conspecifics and prey on call design and intensity

2015· article· en· W2095989382 on OpenAlexaff
Kayleigh Fawcett, David S. Jacobs, Annemarie Surlykke, John M. Ratcliffe

Bibliographic record

VenueBiology Open · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsUniversity of Toronto
FundersNational Research Foundation
KeywordsHuman echolocationBiologyZoologyPredationEcology

Abstract

fetched live from OpenAlex

Echolocating bats are exposed not only to the echoes of their own calls, but often the signals of conspecifics and other bats. For species emitting short, frequency modulated signals e.g. vespertilionoids, adjustments in both the frequency and time domain have been observed in such situations. However, bats using long duration, constant frequency calls may confront special challenges, since these bats should be less able to avoid temporal and frequency overlap. Here we investigated echolocation call design in the highduty cycle bat, Rhinolophus capensis, as bats flew with either a conspecific or heterospecific in a large outdoor flight-room. We compared these recordings to those made of bats flying alone in the same flight-room, and in a smaller flight room, alone, and hunting tethered moths. We found no differences in duty cycle or peak frequency of the calls of R. capensis across conditions. However, in the presence of a conspecific or the vespertilionoid, Miniopterus natalensis, R. capensis produced longer frequency-modulated downward sweeps at the terminus of their calls with lower minimum frequencies than when flying alone. In the presence of the larger high-duty cycle bat, R. clivosus, R. capensis produced shorter calls than when flying alone or with a conspecific. These changes are similar to those of vespertilionoids when flying from open to more cluttered environments. They are not similar to those differences observed in vespertilionoids when flying with other bats. Also unlike vespertilinoids, R. capensis used calls 15 dB less intense in conspecific pairs than when alone.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.106
GPT teacher head0.277
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), 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

Citations33
Published2015
Admission routes1
Has abstractyes

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