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TIME-EXPANSION AND ZERO-CROSSING PERIOD METER SYSTEMS PRESENT SIGNIFICANTLY DIFFERENT VIEWS OF ECHOLOCATION CALLS OF BATS

2001· article· en· W2176902913 on OpenAlexaff
M. Brock Fenton, Sylvie Bouchard, Maarten J. Vonhof, Joanna Zigouris

Bibliographic record

VenueJournal of Mammalogy · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsYork University
Fundersnot available
KeywordsHuman echolocationZero crossingMetreAcousticsZero (linguistics)DetectorGeodesyPhysicsTelecommunicationsComputer scienceGeologyElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

We compared 2 bat detecting systems that use condenser microphones, 1 that performed computer analysis (Anabat6) of the output of a zero-crossing period meter (Anabat system) and the other that performed computer analysis (Canary 1.2) of the output of slowed-down (= time-expanded) recordings (Racal system). The 2 systems provided significantly different pictures of both numbers and characteristics (highest frequency, lowest frequency, and duration) of echolocation calls, whether recorded from free-flying bats in the field or from a stationary bat in the laboratory. Although the AnabatII detector was slightly more sensitive than the QMC S200 detector, the Racal system detected more echolocation calls than the Anabat system; the 19-dB difference in sensitivity was associated with a zero-crossing period meter in the Anabat system. Results suggest 2 recommendations. First, that analysis using zero-crossing period meters should not be used to describe echolocation behavior or calls of bats. Second, that studies of activity and use of habitat based on analysis using zero-crossing period meters should involve calibration against more sensitive bat-detecting systems.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.140

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 head0.034
GPT teacher head0.249
Teacher spread0.215 · 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 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

Citations48
Published2001
Admission routes1
Has abstractyes

Explore more

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