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Record W2072247633 · doi:10.1121/1.2936054

Evaluation of portable high-frequency sonars for diver identification

2008· article· en· W2072247633 on OpenAlexaffabout
Anna Crawford, Vance Crowe, Thomas Pastore, Ronald T. Kessel

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsSonarHarbourUnderwaterIdentification (biology)CraftMarine engineeringSea trialComputer scienceAeronauticsRemote sensingEnvironmental scienceAcousticsEngineeringGeologyOceanographyGeographyArchaeologyArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

Obtaining a positive identification is a critical step in most tiered harbour protection strategies for countering underwater intruders. It is generally recognised that sonar is one of the best tools for underwater imaging, however operating in a harbour environment presents challenges. As part of an on-going harbour protection research project, small easily portable high-frequency sonar systems are being investigated as a means to equip small response craft with intruder identification capability. Several systems are being considered, with the most comprehensive testing by DRDC to date being done on small Canadian-made sonars. Tests were conducted in local harbour waters in Halifax, Canada, and in La Spezia, Italy, through participation in the NATO Undersea Research Centre Response Against Diver Intrusions (RADI) joint trial, conducted in November 2007. A variety of small sonars and manned and unmanned response craft were used during the RADI trial. Evaluation of the performance of these devices for the task of diver identification in realistic conditions will be discussed.

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)0.003
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.000
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 head0.051
GPT teacher head0.288
Teacher spread0.237 · 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.

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

Citations5
Published2008
Admission routes2
Has abstractyes

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