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Record W1505575711

Development of low-cost underwater acoustic array systems for the northern watch technology demonstration project

2011· article· en· W1505575711 on OpenAlexaffvenue
Garry J. Heard, Nicos Pelavas, Carmen E. Lucas, Isaias Peraza, Derek Clark, Colin G. Cameron, VaI Shepeta

Bibliographic record

VenueCanadian acoustics · 2011
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsUnderwaterEngineeringHydrophoneMicrocontrollerEthernetElectrical engineeringComputer scienceComputer hardwareAcoustics
DOInot available

Abstract

fetched live from OpenAlex

The development of low-cost underwater acoustic array systems for the northern watch technology demonstration project is discussed. Developments since the end of the TDP project include upgraded quantization from 16 to 24-bits, an increased sampling rate range from a few Hertz to 240 kHz, reduction in power requirements for each node and the array controller (1.5W), improved digital bus structures with extra data and power pairs, and modernized interfaces including Ethernet and universal serial bus. The arrays for the Northern Watch project have been developed by Omnitech Electronics Inc. as prime under contract to DRDC. The arrays have undergone two prototype developments. The original array design was based on an absolute minimum cost and made extensive use of standard plastic piping and resin materials for the mechanical structure. The new array design also makes use of connectors to allow for hydrophone replacement.

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)0.001
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.038
GPT teacher head0.218
Teacher spread0.180 · 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

Citations9
Published2011
Admission routes2
Has abstractyes

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