MétaCan
Menu
Back to cohort
Record W4229375027 · doi:10.1121/10.0010909

The Littoral Continuous Active Sonar Multi-National Joint Research Project 2014–2020

2022· article· en· W4229375027 on OpenAlexaff
Kevin D. LePage, Alessandra Teseï, Stefano Biagini, S. Lourey, Stefan M. Murphy, Jeffrey R. Bates, Gary Inglis, Paul C. Hines, Gary Wood, Catherine L. Smith, Vicenzo Manzari, Daniele S. Terracciano, Paul van Walree, Doug Grimmett, D. S. Abraham

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2022
Typearticle
Languageen
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsDalhousie UniversityDefence Research and Development Canada
Fundersnot available
KeywordsSonarLittoral zoneMarine mammals and sonarJoint (building)OceanographyComputer scienceOperations researchMarine engineeringMultinational corporationEnvironmental resource managementEnvironmental scienceGeologyEngineeringPolitical scienceCivil engineering

Abstract

fetched live from OpenAlex

One of John Preston's achievements during his career was the hosting of multinational sonar experimentation efforts whilst a scientist at SACLANTCEN. The Littoral Continuous Active Sonar Multi-National Joint Research Project is the most recent international collaborative experimentation activity focused on sonar hosted by NATO STO Centre for Maritime Research and Experimentation, SACLANTCEN's sucessor. Between 2014 and 2020 LCAS brought scientists and engineers from 7 NATO and Partner Nations together with the CMRE to evaluate the effectiveness of continuous active sonar in shallow littoral environments. In this talk, the objectives of the project are laid out, the scientific issues and experimental approach reviewed, details about the four sea trials conducted under LCAS are presented, and a summary of the major results of the project is provided.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.844
Threshold uncertainty score0.625

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.316
Teacher spread0.276 · 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 designNot applicable
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicMaritime Navigation and SafetyFrench-language works237,207