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Record W2897250382 · doi:10.1121/1.5067426

Arctic Beaufort Gyre duct transmission measurements and simulations

2018· article· en· W2897250382 on OpenAlexaboutno aff
Timothy F. Duda, Ying-Tsong Lin, Weifeng G. Zhang, John A. Colosi, Mohsen Badiey

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsnot available
Fundersnot available
KeywordsEddyGeologyDuct (anatomy)OceanographyArcticWater columnOcean gyreBeaufort scaleTransmission lossSound propagationWaves and shallow waterContinental shelfBeaufort seaEnvironmental scienceClimatologyAcousticsMeteorologyPhysicsTurbulence

Abstract

fetched live from OpenAlex

Transmissions of 100–300 Hz sound over distances of 220–505 km in the Beaufort Sea area for 10 months revealed strong long-term trends and short-term variability. The sound was emitted by Canada Basin Acoustic Propagation Experiment (CANAPE) Deep Water sources, and received by CANAPE Shallow Water receivers close to the Chukchi Sea. Much of the sound that arrives at these distances is trapped in the Pacific Water duct. A dynamical model of the area driven by representative forcing, which includes eddies that have propagation consequences, is used to examine changes to the water column at small eddy scales and at broader scales that can influence the sound. Processes such as variable excitation of ducted normal modes, time-variable duct sound-speed mean profile, and coupling of ducted modes to other modes by range dependent eddy features are examined with the model. The effects of these processes are quantified and compared to field observations.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.817
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.041
GPT teacher head0.283
Teacher spread0.243 · 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 designSimulation or modeling
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

Citations3
Published2018
Admission routes1
Has abstractyes

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