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Record W7160887311 · doi:10.1121/10.0040476

Acoustic propagation as an indicator of mesoscale oceanographic features in the Beaufort Sea

2025· article· en· W7160887311 on OpenAlexaboutno aff
William F. Jenkins, Ying-Tsong Lin

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsBeaufort seaMesoscale meteorologyBeaufort scaleArcticSea iceThe arcticSeabed

Abstract

fetched live from OpenAlex

Intrusion of Pacific Summer Water (PSW) and Pacific Winter Water (PWW) into the Arctic Ocean through the Bering Strait leads to the formation of an acoustic duct in the Beaufort Sea. The Beaufort duct is characterized by PSW atop the colder PWW, which itself is colder than the deep polar water beneath. Decades of observation have shown that the Beaufort duct is a persistent and intensifying feature in the Beaufort Sea, with sound propagating hundreds of kilometers under the Arctic ice without ice or seabed interactions. However, fluctuations in its strength were observed during the 2016–2017 Canada Basin Acoustic Propagation Experiment (CANAPE), which suggest a breakdown of the duct between the acoustic sources and receivers. In this study, we review tomographic signals transmitted by the CANAPE sources from the Beaufort Sea received by arrays along the Chukchi Shelf break and analyze how the strength of those receptions can serve as temporal and spatial indicators of mesoscale oceanographic features such as eddies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.966
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.005
GPT teacher head0.228
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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