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Record W1548406203

Characterization of sperm whale vocalization energy based on echolocation signals

2013· article· en· W1548406203 on OpenAlexaff
Hannan Lohrasbipeydeh, Tom Dakin, T. Aaron Gulliver, A. Zieliński

Bibliographic record

Venue2013 OCEANS - San Diego · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSperm whaleHuman echolocationWhaleAcousticsBioacousticsBroadbandEnergy (signal processing)SpermComputer scienceSpeech recognitionPhysicsFisheryMathematicsBiologyTelecommunicationsStatistics
DOInot available

Abstract

fetched live from OpenAlex

Sperm whales (Physeter macrocephalus) emit a train of impulsive echolocation signals called “clicks” when diving in search of food. These acoustic signals can be divided into “usual clicks” and “creaks”. The frequency spectrum of these broadband transient signals is between about 500 Hz and 24 kHz, but most of the energy lies between 2 and 9 kHz. The usual clicks have an inter-click interval (ICI) of 0.5-2 s, whereas the ICI of creaks is less. These click signals consist of multiple pulses which are related to the structure of the sperm whale head. An analysis of these signals is presented based on real data from the Atlantic Undersea Test and Evaluation Center. The motivation is the design of a click energy based sperm whale detector which exploits the characteristics of these signals.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.012
GPT teacher head0.212
Teacher spread0.200 · 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

Citations4
Published2013
Admission routes1
Has abstractyes

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