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Eavesdropping on the echolocation and social calls of bats

2003· article· en· W2166655860 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMammal Review · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsYork University
Fundersnot available
KeywordsHuman echolocationEavesdroppingBiologyCommunicationEcologyComputer sciencePsychologyNeuroscienceComputer security

Abstract

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ABSTRACT 1. Comparisons of original calls and their echoes allow echolocating microchiropteran bats to collect information about their surroundings. Echolocation calls are also a source of information for other animals. A spectacular example is the hearing‐based defence of many species of insects that use echolocation calls to detect marauding bats. The role of echolocation calls remains unknown for bats that eat other bats. 2. Other eavesdroppers, biologists, regularly monitor echolocation calls to collect information about the distribution and patterns of habitat use of echolocating bats. People monitoring echolocation calls have discovered cryptic species of bats. 3. Vocal communication in bats involves social calls that serve only in communication, as well as echolocation calls that influence the behaviour of conspecifics and others. There is evidence of individual‐ and colony‐specific social and echolocation calls. 4. The long age‐spans of bats and the propensity of some species to roost in groups combine with conspicuousness of echolocation calls to set the stage for the discovery of more behavioural interactions mediated by individual‐specific echolocation calls. In the echolocation of microchiropteran bats, signals can serve multiple functions, both for producers and listeners.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.186

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 head0.052
GPT teacher head0.254
Teacher spread0.202 · 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