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Record W4321483470 · doi:10.1121/10.0017325

Under-ice mid-frequency acoustic transmission and communication in two Arctic Ocean environments

2023· article· en· W4321483470 on OpenAlexaboutno aff
Dag Tollefsen, Paul van Walree, Trond Jenserud, Vidar Forsmo

Bibliographic record

VenueJASA Express Letters · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsnot available
FundersForsvaret
KeywordsGeologyArcticThe arcticSea iceTransmission lossCanada BasinBeaufort seaImpulse (physics)OceanographyEnvironmental scienceAcousticsPhysics

Abstract

fetched live from OpenAlex

This paper presents data from mid-frequency (4-8 kHz) under-ice acoustic transmission and communication experiments in the Nansen Basin and in the Beaufort Sea of the Arctic Ocean. Measured impulse responses to range ∼10 km showed considerable delay spread between distinct groups of arrivals due to surface-ducted and bottom-reflected paths. The relative strengths of these groups depend on duct and under-ice properties. We demonstrate that despite shallow (∼25 m) source/receiver depths, good communication performance can be achieved in both environments when exploiting the bottom-reflected arrivals. Simulations with the Bellhop ray model support the findings.

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 score0.307
Threshold uncertainty score0.513

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 head0.024
GPT teacher head0.261
Teacher spread0.237 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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