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Record W2055710014 · doi:10.4043/25525-ms

Virtual Arctic Simulation Environment

2015· article· en· W2055710014 on OpenAlexaff
Matthew Hamilton, Stephen G. Dodd

Bibliographic record

VenueOTC Arctic Technology Conference · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsGRi Simulations (Canada)
Fundersnot available
KeywordsSubseaRemotely operated underwater vehicleBathymetryVisualizationMarine engineeringSonarDredgingComputer scienceGraphicsArcticRemotely operated vehicleVirtual realityGeologyEngineeringComputer graphics (images)Human–computer interactionOceanographyMobile robotRobot

Abstract

fetched live from OpenAlex

Abstract We present a virtual software simulation system for remotely-operated vehicle (ROV) operations in arctic and harsh environments particularly focused on subsea trenching. The system provides interactive, three-dimensional graphics and dynamics simulation with high fidelity. In addition to standard ROVs, the system can now simulate trenching and dredging vehicles such as jetters and ploughs. It also provides support for integration of data for visualization and analysis from a wide range of sources including sub-bottom imaging, seismic, bathymetry and sidescan sonar. Visualizations can be controlled to enhance features important for geological and geotechnical analysis.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.997

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.004

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 head0.023
GPT teacher head0.234
Teacher spread0.210 · 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 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

Citations1
Published2015
Admission routes1
Has abstractyes

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