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Record W1993054047 · doi:10.1121/1.4778970

Shallow-water reverberation highlights and bottom parameter extractions from the STRATAFORM

2002· article· en· W1993054047 on OpenAlexaff
John R. Preston, Dale D. Ellis

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsReverberationScatteringSonarAcousticsGeologyWaves and shallow waterBoundary (topology)OpticsPhysicsMathematicsOceanography

Abstract

fetched live from OpenAlex

Together with SACLANTCEN, the authors recently participated in the Boundary Characterization Experiment to measure shallow-water bottom reverberation in the STRATAFORM off New Jersey. SUS charges were used as monostatic sources. The receivers were horizontal arrays. Data were analyzed in bands from 160–1500 Hz. The STRATAFORM is known to have benign surface morphology but contains many buried river channels. Highlights of the reverberant returns are discussed that include returns from over the shelf break. Some comparisons in reverberation characteristics between SUS and coherent pulses are noted. Another objective of these reverberation experiments was to quickly invert for bottom scattering and bottom loss parameters. An automated geo-acoustic parameter extraction method was used together with the Generic Sonar Model and a Jackson-Mourad model for scattering. After automatically adjusting bottom loss and scattering strength, good agreement is achieved between the diffuse reverberation data and model predictions in relatively flat areas. Model/data differences are generally correlated with bottom scattering features. Since reverberation typically lasts 10–20 s or more, extracted parameters apply over wide areas. Local bottom loss and backscattering measurements were made by Holland in these areas. A comparison with Holland’s results is given. [Work supported by ONR Code 32, Grant No. N00014-97-1-1034.]

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.688
Threshold uncertainty score0.999

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 science0.0010.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.241
Teacher spread0.213 · 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.

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

Citations5
Published2002
Admission routes1
Has abstractyes

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