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Record W2994396607

Array element localization of a bottom moored hydrophone array

2002· article· en· W2994396607 on OpenAlexaffvenue
Matthew Barlee, Stan E. Dosso, Philip W. Schey

Bibliographic record

VenueCanadian acoustics · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHydrophoneAcousticsSensor arrayInversion (geology)Underwater acousticsArray processingComputer scienceEngineeringGeologySignal processingElectronic engineeringPhysicsUnderwaterSeismologyOceanography
DOInot available

Abstract

fetched live from OpenAlex

In ocean acoustics, rapidly deployable, autonomous, bottom moored hydrophone arrays allow for quick, cost effective deployment, but result in poor knowledge of sensor positions.Because ad vanced array processing techniques, such as M atched Beam Processing, are highly sensitive to errors in sensor location, an accurate assessment of hydrophone positions is necessary.This paper discusses array element localization (AEL) and its use in localizing the ULITE array, a horizontal array deployed in the Timor Sea during the 1998 RDS-2 trial.The ill-posed inverse problem of determ ining source (imploded light bulbs) and receiver positions from the relative arrival times of source transients is solved through regularized linearized inversion.The inversion solution fits the d a ta to high precision and provides individual hydrophone position estimates th a t provide the sm oothest array shape th a t is consistent with the acoustic data. RÉSUMÉLes systèmes acoustiques m arins qui sont rapidement déployés au fond de la mer, et qui fonctionnent avec autonomie, offrent une méthode de recherche qui est de faible cout, mais qui donne une pauvre connaissance de les positions des récepteurs.Pacreque la validité des manipulations des donnés, comme celles obtenues par le Matched Beam Processing, est fortement dépendente sur la location des instrum ents, une précise determ ination de la position de l'instrument est nécessaire.Ce papier décrit la méthode de Localization des Éléments d 'Étalage (AEL) et son utilization dans la localization du système ULITE, un étalage horizontal déployé dans la mer de Timor pendant l'essai RDS-2 de l'an 1998.La question iverse mal posée, celle de la determination des positions de les sources (des ampoules implosées) et les récepteurs par les tems d 'arivee relatifs des transients de source, est résolu par l'inversion linéale régularisée.La solution d 'inversion est une excellente réprésentation de les donnés, et donne les positions de chaque hydrophone en accordance avec un model qui donne la forme optimale a l'étalage acoustique, et qui est consistent avec les donnés acoustiques.Vol. 30 No. 4 (2002) -

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.213
Teacher spread0.192 · 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 designBench or experimental
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
Published2002
Admission routes2
Has abstractyes

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