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Record W2037346990 · doi:10.1121/1.4809427

Twenty years of barrel-stave flextensional transducer technology in Canada

2005· article· en· W2037346990 on OpenAlexaboutno aff
Dennis F. Jones

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsTransducerAcousticsUnderwaterSonarGeologySubmarineMarine mammalHumpback whaleHuman echolocationUnderwater acousticsOceanographyWhaleSeismologyPhysicsFisheryBiology

Abstract

fetched live from OpenAlex

The barrel-stave flextensional transducer, a compact underwater sound source, was conceived at DRDC Atlantic in 1986 [G. W. McMahon and D. F. Jones, U.S. Patent No. 4,922,470 (1 May 1990); Canadian Patent No. 1,285,646 (2 July 1991)]. Over the years, five barrel-stave designs belonging to three flextensional classes were built and tested at DRDC Atlantic. Three Class I transducers with operating frequencies ranging from 800 to 1600 Hz were integrated into submarine communications buoys, low frequency active horizontal projector arrays, and a broadband sonar towbody. A high-power Class II and broadband (1–7 kHz) Class III transducer were deployed under the ice in the Lincoln Sea for research related to rapidly deployable surveillance systems. These barrel-stave flextensional transducers have also supported a variety of marine mammal studies including vocal mimicry in long-finned pilot whales, coda dialects in sperm whales, and the R&D of acoustic detection and tracking systems for endangered northern right whales. In August 2004 a barrel-stave transducer was used to lure a trapped juvenile humpback whale to the sluice gates of a tidal generating station on the Annapolis River in Nova Scotia by transmitting humpback whale calls underwater. The acoustic performance parameters for all 5 transducers will be presented.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.135
Threshold uncertainty score0.272

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.004

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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2005
Admission routes1
Has abstractyes

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