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Record W4367309860 · doi:10.3390/acoustics5020026

Implication of Altered Acoustic Active Space for Cetacean Species That Result from Soundscape Changes and Noise Additions

2023· article· en· W4367309860 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

VenueAcoustics · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of VictoriaFisheries and Oceans Canada
Fundersnot available
KeywordsSoundscapeSpace (punctuation)HabitatEcologyMetric (unit)PredationNoise (video)Focus (optics)Abundance (ecology)Computer scienceBiologySound (geography)AcousticsArtificial intelligencePhysicsEngineering

Abstract

fetched live from OpenAlex

Organisms use multi-modal, scale-dependent, sensory information to decipher their surroundings. This can include, for example, recognizing the presence of con- or heterospecifics, including a predatory threat, the presence and abundance of prey, or navigational cues to travel between breeding or feeding areas. Here we advocate for the use of the concept of active space to understand the extent to which an individual might be sending and receiving habitat information, describing this as the active component of their niche space. We present the use of active space as a means to understand ecological interactions, giving focus to those species whose active space is acoustically defined, in particular, cetacean species. We show how the application of estimates of active space, and changes in extent, can help better understand the potential disturbance effects of changes in the soundscape, and be a useful metric to estimate possible adverse effects even when stress responses, or behavioral or calling modifications are not obvious.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score0.484

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 head0.040
GPT teacher head0.260
Teacher spread0.220 · 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