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International harmonization of procedures for measuring and analyzing of vessel underwater radiated noise

2021· review· en· W4200507539 on OpenAlexaffabout
Michael A. Ainslie, Bruce Martin, Krista Trounce, David Hannay, Justin Eickmeier, Terry J. Deveau, Klaus Lücke, Alexander O. MacGillivray, Véronique Nolet, Pablo Borys

Bibliographic record

VenueMarine Pollution Bulletin · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsTransport CanadaFraser Health
Fundersnot available
KeywordsStandardizationUnderwaterHarmonizationPort (circuit theory)Noise (video)BayMarine engineeringEnvironmental scienceComputer scienceEnvironmental resource managementGeographyTelecommunicationsEngineeringArchaeologyAcousticsArtificial intelligenceElectrical engineering

Abstract

fetched live from OpenAlex

The habitat of the endangered southern resident killer whale (SRKW) overlaps major international shipping lanes near the Port of Vancouver, British Columbia. Shipping is a dominant source of underwater noise, which can hinder SRKW key life functions. To reduce environmental pressure on the SRKWs, Vancouver Fraser Port Authority offers incentives for quieter ships. However, the absence of a widely accepted underwater radiated noise (URN) measurement procedure hinders the determination of relative quietness. We review URN measurement procedures, summarizing results to date from two Canadian-led projects aimed at improving harmonization of shallow-water URN measurement procedures: One supports the International Organization for Standardization (ISO) in the development of a URN measurement standard; the other supports the alignment of URN measurement procedures developed by ship classification societies. Weaknesses in conventional shallow-water URN metrics are identified, and two alternative metrics proposed. Optimal shallow-water measurement geometry is identified.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.271
Teacher spread0.235 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations38
Published2021
Admission routes2
Has abstractyes

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