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Record W2891294947 · doi:10.1121/2.0000854

Acoustical measurement, processing, reporting and terminology standards for underwater risk assessment

2017· article· en· W2891294947 on OpenAlexaff
Michael A. Ainslie, Christ A. F. de Jong, Michele B. Halvorsen, Darlene R. Ketten, Mark K. Prior, David Hannay

Bibliographic record

VenueProceedings of meetings on acoustics · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsUnderwaterSound exposureMetric (unit)Computer scienceConsistency (knowledge bases)Environmental scienceAcousticsSound (geography)EngineeringGeologyArtificial intelligence

Abstract

fetched live from OpenAlex

Anthropogenic underwater sounds represent a potential risk to aquatic organisms. Many regulators require this risk to be assessed before allowing a sound-producing activity to proceed. Regulators typically set exposure criteria for a range of acoustic parameters and require the assessment to address whether a given acoustic metric would exceed a specified allowable threshold. While the value of the threshold is usually clear, the procedure required to calculate the metric sometimes lacks sufficient detail, leading to uncertainties and potential inconsistencies in interpretation. Procedures are described that enable intra- and inter-project consistency in use, processing, and reporting of metrics. Quantities derived from sound pressure and sound particle motion are considered, providing metrics relevant to assessments for fish, aquatic invertebrates, and aquatic mammals. Specific metrics for which procedures are described include transient duration, zero-to-peak quantities, mean-square and time-integrated-squared quantities (e.g., sound exposure), and their spectral densities. The metrics are relevant to ambient sound and to specified activities such as drilling, pile-driving, seismic imaging, or dynamic positioning. Issues addressed include the specification of fractional octave and fractional decade bands, and the harmonization of units and reference values used for reporting. Continuing efforts on standards for the characterization of underwater sound sources are described.

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)0.005
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.066
GPT teacher head0.341
Teacher spread0.276 · 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.

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
Published2017
Admission routes1
Has abstractyes

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