MétaCan
Menu
Back to cohort
Record W2013584112 · doi:10.1121/1.4773109

Radiated underwater noise levels of two research vessels, evaluated at different acoustic ranges in deep and shallow water

2012· article· en· W2013584112 on OpenAlexaboutno aff
Anton Homm, Stefan Schäl

Bibliographic record

VenueProceedings of meetings on acoustics · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsnot available
Fundersnot available
KeywordsHullUnderwaterNoise (video)Marine engineeringAcousticsRange (aeronautics)Sound (geography)Environmental scienceDeep waterGeologyOceanographyComputer scienceEngineeringAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

Within the scope of a NATO research project on onboard signature management, an extensive international measurement campaign was carried out in 2011. Two naval research vessels, CFAV Quest from Canada and FS Planet from Germany, were participating in the program. Both ships were ranged at Loch Fyne (UK), at open seas, in Heggernes (Norway), in Aschau (Germany), and Brest (France). One of the objectives of the research program is the evaluation of differences in reported underwater acoustical radiated noise levels of the ships under various boundary conditions. Quest and Planet sailed with a number of fixed machinery configurations like slow speed, high speed, and shaker excitation at certain structural points at each measurement site, respectively. The environmental conditions comprised deep water and shallow water as well as free field conditions at open seas. Both vessels are equipped with a large number of accelerometers, located at the main noise sources and along the hull frames of the ships. Additionally, at each acoustic range, runs with a towed sound source as a reference source were performed. In the presentation, a comparison of the first results of the radiated noise levels will be given.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.071
GPT teacher head0.318
Teacher spread0.247 · 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 designBench or experimental
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

Citations2
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of meetings on acousticsSame topicUnderwater Acoustics ResearchFrench-language works237,207