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Record W1963732123 · doi:10.2118/149203-ms

1000 Km of Under Ice Seabed Survey with an AUV

2011· article· en· W1963732123 on OpenAlexfundaboutno aff
Richard Mills, James Fergsuon, Jean-Marc Laframboise, Chris Kaminski, Tristan Crees

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersNatural Resources CanadaMemorial University of Newfoundland
KeywordsPayload (computing)Sea iceOceanographyBathymetryCruiseArcticMarine engineeringGeologyMeteorologyGeographyEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract In March and April 2010, an ISE Explorer Autonomous Underwater Vehicle (AUV), built for Natural Resources Canada (NRCan), was deployed to Canada's high Arctic. Its mission was to undertake under-ice bathymetric surveys in support of Canada's submission to establish the outer limits of its continental shelf under the United Nations Convention on the Law of the Sea (UNCLOS). During this deployment several under-ice records were broken and several new technologies were demonstrated. NRCan's AUV is an ISE Explorer class vehicle, with several innovative additions to make it suitable for arctic survey work. Most notable are a 4000 m depth rated variable ballast system, a 1500 Hz long-range homing system, and under-ice charging and data transfer capabilities. A Short-Range Localization (SRL) system was also developed for close range positioning. The homing and SRL systems were developed by Canadian defense scientists and engineers at DRDC (Defence Research and Development Canada). The Explorer's range was extended to approximately 450 km by adding a hull section to accommodate extra batteries. The scientific payload onboard included a Seabird SBE49 Conductivity-Temperature-Depth (CTD) sensor, Knudsen singlebeam echosounder, and a Kongsberg Simrad EM2000 multibeam echosounder. In order to optimize battery endurance, the plan was to only turn on the EM2000 at strategic locations (i.e. potential sea mounts) along the mission path. The Main Camp near Borden Island (78°14’N, 112°39’W) was the launch site for the AUV. It was launched from an 8 m by 3 m ice hole, cut through 2 – 3 m thick ice. After several test dives, the first mission was a transit to a Remote Camp, 320 km to the northwest. The AUV autonomously homed into the Remote Camp and was secured with the help of a small remotely operated vehicle (ROV). Without being removed from the water, it was charged and survey data was downloaded, all through a 1.3 m by 2 m ice hole. Subsequently, a second survey mission was undertaken in a region known as the Sever Spur (~79°N, 115°W), which returned back to the Remote Camp. Finally, it embarked on a return transit mission to the Main Camp for recovery. The AUV spent 10 days under ice before being successfully recovered. In total, close to 1000 km of under-ice survey was accomplished between the 3 missions. The AUV reached depths of 3160 m and transited at an average speed of 1.5 m/s at an altitude of 130 m above the seabed. From operating entirely under ice, to surveying in such a challenging environment, to the distances and objectives, this is an historic milestone in AUV and polar science. ISE, DRDC and NRCan are now preparing for a 2011 deployment to collect additional arctic survey data.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.212
Teacher spread0.174 · 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 designObservational
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
Published2011
Admission routes2
Has abstractyes

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