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Record W4243854887 · doi:10.22564/rbgf.v33i4.954

ACOUSTIC RESPONSE OF AMAZON SHELF MUDDY SEDIMENTS

2015· article· en· W4243854887 on OpenAlex
Pedro S. Menandro, Alex Cardoso Bastos, Valéria da Silva Quaresma, Susana B. Vinzón

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBrazilian Journal of Geophysics · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsContinental (Canada)
FundersMinisterio de Economía y Competitividad
KeywordsGeologySeabedEcho soundingOceanographySedimentContinental shelfBathymetryDredgingBackscatter (email)MineralogyGeomorphology

Abstract

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ABSTRACT. Understanding the behaviour of acoustic signals in marine sediments is of great importance for applied coastal studies. In areas with high suspended sediment concentration, the detection and delineation of these fluid mud layers are imperative for the determination of nautical depths (navigability) and dredging projects. Herein, we investigate the response of the acoustic signal according to the frequency and surface sediments characteristics (grain size and density). The dataset was collected along the Amazon inner shelf (North Brazil), including high-frequency acoustic data (3.5, 33 and 210 kHz), surface sediment physical properties, in situ bottom density and suspended particulate matter derived from optical backscatter sensors. Results show a cross-shelf transition from a sandy to a muddy bottom, followed by a decrease in sediment seabed density. Acoustic data also show this transition, illustrated by different levels of signal penetration. Statistical analysis relating the geophysical records and the physical properties of the sediments showed that density was a determining variable for the interpretation of surface acoustic reflection. The acoustic sources were able to detect the occurrence of fluid mud layers but the optical backscatter sensor had the best resolution in delineating the upper boundary of the fluid mud layer. The sub-bottom profiler (3.5 kHz) detected the fluid mud layers, whereas the echo displacement were not always related to the presence of fluid mud. Finally, the results pointed out that for coastal engineering projects and navigation purposes, the mapping of seabed density along with geophysical surveys is effective, and highlighted the issue about delineation of upper fluid mud boundary.Keywords: geoacoustic, fluid mud, Amazon River. RESUMO. Fundamental para estudos aplicados a regiões costeiras, a geoacústica submarina auxilia na compreensão do comportamento do sinal acústico no sedimento marinho. A detecção de depósitos lamosos em registros acústicos de alta resolução é de fácil distinção, aparecendo normalmente como pacotes sedimentares de baixa reflexão. Em áreas com alta concentração de material particulado em suspensão, a detecção e a delimitação dessas camadas de lama fluida são fundamentais para a determinação da profundidade náutica e para realização de projetos de dragagem. Esse estudo tem como principal objetivo investigar variações no sinal acústico de diferentes fontes, de acordo com a frequência e as características do sedimento superficial (granulometria e densidade). A base de dados analisada foi coletada na Plataforma Interna do Canal Norte do Rio Amazonas, e é composta por registros geofísicos de alta frequência (3,5, 33, 210 kHz), propriedades físicas do sedimento superficial, densimetria in situ e medidas de material particulado em suspensão. Os resultados sedimentológicos e geofísicos mostram uma transição de um fundo arenoso para lamoso na plataforma continental, acompanhada por uma diminuição na densidade do sedimento superficial do fundo marinho. A análise estatística apontou a densidade como variável determinante para interpretação da reflexão superficial do sinal acústico. As fontes acústicas foram capazes de detectar a ocorrência da lama de fluida, mas o sensor óptico obteve a melhor resolução para delinear o limite superior da camada de lama fluida. O perfilador de sub-fundo (3,5 kHz) registrou camadas transparentes que indicam a presença de estratos sedimentares pouco consolidados, enquanto o deslocamento do eco registrado pela ecobatimetria nem sempre foi relacionado unicamente com a presença de lama fluida. Finalmente, os resultados apontaram que para projetos de engenharia costeira e com fins de navegação, o mapeamento da densidade fundo do mar em conjunto com levantamentos geofísicos é eficaz, além de destacar essa questão da delineação do limite superior da lama fluida. Palavras-chave: geoacústica, lama fluida, Rio Amazonas.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.434

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 studies0.0000.000
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 head0.028
GPT teacher head0.268
Teacher spread0.240 · 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