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Record W2087699187 · doi:10.1121/1.3588272

Why do Weddell seals shout?

2011· article· en· W2087699187 on OpenAlexaff
Jack Terhune

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsUnderwaterOctave (electronics)Noise (video)GeologyRange (aeronautics)AmplitudePhysicsAcousticsGeodesyMaterials scienceOceanographyOpticsComposite material

Abstract

fetched live from OpenAlex

Source levels (SLs) of Weddell seal (Leptonychotes weddellii) underwater calls near Mawson, Antarctica, were determined using a two hydrophone array. SLs were 161 ± 10 dB re 1 μPa m (range 135–179, n = 280). SLs from 0.1–6 kHz varied little with frequency (r2 = 0.02, t = −2.46, P = 0.01, n = 251). One-sixth octave ambient noise levels (ANLs) from 0.1–6 kHz were measured on low (n = 1), medium (n = 7), and high (n = 7) noise level days. The ANLs were flat (0.1–6 kHz) and the mean 1/6 octave ANLs were 77 ± 2.8, 96 ± 6.5, and 110 ± 6.1 dB re 1 μPa. SLs were randomly paired against ANLs in a Monte Carlo (n = 100 000) model to calculate the seal communication ranges (m), assuming spherical spreading and received levels 20 dB above threshold. The mean communication ranges for low, medium, and high ANLs were 2806 ± 2718, 428 ± 662, and 83 ± 124 m, respectively (median distances were 2006, 205, and 43m). The distributions were highly skewed toward the shorter distances. The high amplitude calls of Weddell seals may have evolved to facilitate local communication under noisy conditions rather than for very long range purposes.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.241
Teacher spread0.216 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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