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Record W2008840997 · doi:10.1121/1.4808330

Under-ice ambient noise in Eastern Beaufort Sea, Canadian Arctic, and its relation to environmental forcing

2013· article· en· W2008840997 on OpenAlexafffundabout
G. Bazile Kinda, Yvan Simard, Cédric Gervaise, Jérôme I. Mars, Louis Fortier

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversité du QuébecUniversité LavalResponse Biomedical (Canada)Université du Québec à Rimouski
FundersNatural Sciences and Engineering Research Council of CanadaArcticNet
KeywordsSea iceArctic ice packDrift iceGeologyArcticAmbient noise levelOceanographyOcean gyreAntarctic sea iceClimatologyFast iceSea ice thicknessArctic sea ice declineNoise (video)Beaufort seaPlumeEnvironmental scienceSound (geography)MeteorologyGeography

Abstract

fetched live from OpenAlex

This paper analyzes an 8-month time series (November 2005 to June 2006) of underwater noise recorded at the mouth of the Amundsen Gulf in the marginal ice zone of the western Canadian Arctic when the area was >90% ice covered. The time-series of the ambient noise component was computed using an algorithm that filtered out transient acoustic events from 7-min hourly recordings of total ocean noise over a [0-4.1] kHz frequency band. Under-ice ambient noise did not respond to thermal changes, but showed consistent correlations with large-scale regional ice drift, wind speed, and measured currents in upper water column. The correlation of ambient noise with ice drift peaked for locations at ranges of ~300 km off the mouth of the Amundsen Gulf. These locations are within the multi-year ice plume that extends westerly along the coast in the Eastern Beaufort Sea due to the large Beaufort Gyre circulation. These results reveal that ambient noise in Eastern Beaufort Sea in winter is mainly controlled by the same meteorological and oceanographic forcing processes that drive the ice drift and the large-scale circulation in this part of the Arctic Ocean.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.964

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 head0.008
GPT teacher head0.192
Teacher spread0.184 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations85
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicArctic and Antarctic ice dynamicsFrench-language works237,207