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Record W2011876269 · doi:10.4043/22106-ms

Real-Time Pack Ice Monitoring Systems - Identification of Hazardous Sea Ice Using Upward Looking Sonars for Tactical Support of Offshore Oil and Gas Projects

2011· article· en· W2011876269 on OpenAlex
David B. Fissel, Todd Mudge, R.A.J. Chave, Matt Stone, Anudeep Kanwar, Adam Z. Bard, Jan Buermans

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOTC Arctic Technology Conference · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsASL Environmental Sciences (Canada)
FundersDivision of Ocean SciencesFisheries and Oceans Canada
KeywordsSea iceFast iceArctic ice packSubmarine pipelineDrift iceGeologyOceanographySea ice thicknessAntarctic sea iceIcebergArcticKeelSeabed gouging by iceSonar

Abstract

fetched live from OpenAlex

Abstract There is an increasing requirement for real-time detection of sea ice hazards. These hazards include the identification of thick ice keels, large hummocky ice, fast moving ice, rapidly changing ice direction and multi-year ice. Such information is needed in real-time to support tactical applications for safe routing of ships in heavy sea ice concentrations. More recently, a need has emerged for tactical support of offshore oil and gas activities in ice infested waters of the Arctic Ocean and in marginal ice areas such as the Barents Sea, the Sea of Okhotsk, the Caspian Sea, Baffin Bay, the Labrador Sea and East Greenland waters. Reliable upward looking sonar (ULS) instruments, including the ASL Ice Profiler for ice keel measurements and the Acoustic Doppler Current Profiler for Ice Velocity measurements have been widely used in these areas for many years. These instruments, which record data internally, are operated from subsurface moorings that are deployed and recovered by ship during times of minimal sea ice coverage. Providing real-time measurements from the upward looking sonar measurements operating under heavy ice cover pose new technological challenges. The use of surface buoys to relay data from subsurface instruments to shore facilities or satellites is not possible due to the ice cover itself. A more feasible approach is to transmit the data from each instrument using underwater cables on the sea floor and which link the instruments on the subsurface moorings to a bottom mounted or floating structure. For a floating structure, the use of high performance acoustic modems may be required. Previous experience with real-time ULS ice measurement systems dates back to operational projects undertaken from 2002 to the present. More challenging requirements for real-time ULS ice measurement systems are being addressed in much deeper and more remote areas of the Arctic Ocean such as the Barents and Beaufort Seas. Conditions in these areas can vary from short episodes of hazardous ice to more prolonged and severe ice conditions. ULS ice systems may be deployed on a yearround basis or used episodically strategically just before hazardous ice episodes begin. The requirements for timely and accurate ice information demand high reliability in support of ship navigation, offshore oil and gas drilling and development applications. The real-time ULS ice measurement system must be capable of operating for multiple years without servicing in conjunction with other metocean sensors packages (e.g. ice radar, satellite, winds). Multiple ULS measurement arrays will be needed over operational areas spanning distances of many kilometers. For these Arctic Ocean applications, cabled ocean observatory technology and advanced underwater acoustic modems become key enabling technologies.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score0.755

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)0.0000.000

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 head0.035
GPT teacher head0.247
Teacher spread0.212 · 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