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Record W4241638341 · doi:10.1142/s0218396x00000212

MATCHED FIELD TOMOGRAPHIC INVERSION TO DETERMINE RANGE DEPENDENT GEOACOUSTIC PROPERTIES

2000· article· en· W4241638341 on OpenAlex

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

VenueJournal of Computational Acoustics · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsBroadbandInversion (geology)ReplicaRange (aeronautics)GeologyTomographyAcousticsComputer scienceSeismologyOpticsTelecommunicationsPhysicsMaterials science

Abstract

fetched live from OpenAlex

The paper describes a new broadband tomographic matched field method for estimating the geoacoustic properties of a range-dependent shallow water environment. This method is designed for a multiple acoustic element configuration (several sources and vertical arrays deployed in an ocean region) in order to estimate the range and cross-range properties of the sediment over the region. The synthetic pressure fields (replicas) for the tomographic inversion are computed using a ray model. A linear processor operating in the frequency domain is used to quantify the match between replica and measured fields. This processor is based on coherent summations over frequencies and receiver pairs. The method is demonstrated for a geoacoustic ocean model simulating the environment of the Haro Strait experiment. The area is divided into cells in which the geoacoustic properties are range independent but can vary from one cell to another. The layer thickness can vary within a cell. Results are presented for the estimation of the compressional velocity and sediment layer thickness in the ideal case of a noise free synthetic data set.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.998

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)0.0030.000

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