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Record W2242983954

Flow of Ice through Long Converging Channels

2007· article· en· W2242983954 on OpenAlexvenueno aff
Ivana Kubat, Mohamed Sayed, Stuart B. Savage, Tom Carrières

Bibliographic record

VenueNPARC · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyPressure ridgeAdvectionMechanicsSea iceFlow (mathematics)Drift iceArctic ice packClimatologyPhysicsThermodynamics
DOInot available

Abstract

fetched live from OpenAlex

This paper examines some issues of the flow of ice in long and converging channels which may affect navigation. The emphasis is on pressure distributions and the role of ice properties and tidal currents. The present work employs an ice dynamics model that is based on a viscous plastic constitutive model with an elliptical yield envelope, the thickness redistribution model of Savage (2007), and a Particle-In-Cell (PIC) advection approach. Pressure distributions are obtained for an idealized geometry and uniform wind forcing. The results indicate that zones of relatively low pressures develop along the centre of the channel. Increasing the shear strength of the ice cover leads to somewhat lower pressures within such zones along the centre of the channel. That reduction of pressure is caused by the increased transfer of wind forces to land boundaries. Tides are shown to generally decrease pressures. The tidal currents also increase the overall drift, although drift slows and even reverses direction during parts of the tidal cycle.

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)0.001
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.222
Teacher spread0.209 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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Same venueNPARCSame topicArctic and Antarctic ice dynamicsFrench-language works237,207