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10.1016/0967-0653(96)80674-p

2000· article· en· W73398933 on OpenAlexvenueno aff
R.G.J. Winchester

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsnot available
Fundersnot available
KeywordsSubseaUnderwaterRelation (database)Systems engineeringEngineeringReliability (semiconductor)Investment (military)Remotely operated underwater vehicleEngineering managementPropulsionOperations researchRisk analysis (engineering)Computer scienceMarine engineeringBusinessOceanographyArtificial intelligence

Abstract

fetched live from OpenAlex

The needs of undersea defense, and indeed those of the scientific community, overlap those of the offshore oil and gas industry, not least when it comes to subsea operations. They share problems encountered in the design and use of unmanned underwater vehicles, particularly in relation to reliability, efficiency, cost-effectiveness, and capabilities. The U.K. Marine Technology Directorate Ltd. (MTD) is managing a research program - Technology for Unmanned Underwater Vehicles (TUUV) - formulated with the particular aim of solving the problems identified by industry in relation to the operation of UUVs. The overall goal of the first three TUUV phases is to provide a convincing demonstration that the production of such advanced systems is practical, credible and cost-effective. Despite the advances in TUUV1, discussions with operators and program participants show that broad concerns over vehicle operations remain. TUUV2 and TUUV3 will transform the current purely technical and largely independent projects into an integrated concept demonstration that will justify the mainly industrial investment needed to make TUUV4 a reality in time for the millennium.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.904
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9860.996

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 head0.008
GPT teacher head0.160
Teacher spread0.152 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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