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Record W2346891384 · doi:10.1121/1.4950551

Potential impacts of climate change on acoustic propagation in the Arctic

2016· article· en· W2346891384 on OpenAlexaboutno aff
Timothy F. Duda, Lee Freitag, Lori Adornato, Robert H. Byrne

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsArcticRefractionAbsorption (acoustics)Environmental scienceThe arcticTransmission lossAtmospheric sciencesGeologyOceanographyAcousticsOpticsPhysics

Abstract

fetched live from OpenAlex

Some forecasts show surface pH in the Arctic dropping from 8.1 to 7.6 over the next 100 years. This substantial decrease may cause changes in acoustic transmission at frequencies where the pH-dependent borate absorption plays a role, below about 5 kHz. In many cases, upward refraction of sound in the near-isothermal Arctic waters causes ice or surface scattering effects to dominate transmission. However, recent observations in the Canada Basin show that 700 and 900-Hz sound can be fully ducted beneath the Pacific Summer Water, with no ice interaction, and be detectable over distances of a few hundred kilometers. In this situation, the received signal level is controlled largely by cylindrical spreading and absorption. Here, for a wide band of frequencies, the effects of probable pH reductions and reduced absorption are investigated using a few models of pH depth profiles. There is potential for increased signal levels of 5 dB or more for 200-km propagation if the duct waters have significantly reduced pH.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.225
Teacher spread0.214 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of America→Same topicArctic and Antarctic ice dynamics→French-language works237,207→