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Record W1548406203

Characterization of sperm whale vocalization energy based on echolocation signals

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

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

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score1.000

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)0.0200.001

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 head0.012
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