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Record W4300494219 · doi:10.5957/icetech-2012-129

Numerical Simulations of Ice Interaction with a Moored Structure

2012· article· en· W4300494219 on OpenAlexaff
Mohamed Sayed, Ivana Kubat, Brian Wright, Aleksandr Iyerusalimskiy, Amal C. Phadke, Brenda K. Hall

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsConocoPhillips (Canada)National Research Council Canada
Fundersnot available
KeywordsSea iceGeologyDrift iceMooringSea ice thicknessRange (aeronautics)Arctic ice packNumerical modelsMeteorologyClimatologyGeophysicsOceanographyAerospace engineeringNumerical modelingEngineeringPhysics

Abstract

fetched live from OpenAlex

Numerical simulations are carried out to represent the historical data of ice interaction with the Kulluk during the 1980s. Three dimensional simulations include dynamics of the ice cover and the response of the mooring system. The results give modes of ice accumulation, clearing and ice forces. Depth-averaged simulations consider larger zones of the ice cover to examine a range of conditions that were observed during the past operation of the Kulluk in the Beaufort Sea. The simulations evaluate the effects of managed ice cover characteristics such as floe sizes and confinement. Predicted forces are compared to the historical record of measurements.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.009
GPT teacher head0.220
Teacher spread0.211 · 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 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

Citations2
Published2012
Admission routes1
Has abstractyes

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