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Record W2000632312 · doi:10.3189/002214308785836986

Effects of sample size, centrifugal acceleration and brine inclusions on the elastic modulus of sea ice

2008· article· en· W2000632312 on OpenAlexafffund
Michael Lau, Stephen J. Jones, Ryan Phillips

Bibliographic record

VenueJournal of Glaciology · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsMemorial University of NewfoundlandNational Research Council CanadaCentre For Cold Ocean Resources EngineeringCommunity Sector Council Newfoundland and Labrador
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBrineGeologySea iceSea ice growth processesModulusElastic modulusCentrifugal forceMechanicsGeotechnical engineeringMineralogyArctic ice packMaterials scienceSea ice thicknessComposite materialThermodynamicsOceanography

Abstract

fetched live from OpenAlex

Abstract We present a re-analysis of the results obtained from a series of measurements on freshwater and saline ice beams under various centrifugal accelerations. The data show a strong influence of beam size, brine volume and centrifugal acceleration on the elastic modulus of ice. The data suggest a transition brine volume at around 9%, which might occur close to the melting point, at which the elastic modulus of ice drops rapidly due to a possible change of brine-pocket structure. Furthermore, for brine volumes less than 9%, there is a negligible increase in the elastic modulus measured under high centrifugal acceleration, but for brine volumes more than 9% the increase is considerable, approaching that measured with freshwater ice. This may be due to necking of brine drainage channels just above the ice/water interface at high centrifugal acceleration. A model of sea ice was constructed based on existing theories of brine inclusions in sea ice, which satisfactorily predicts the observed trends.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.171

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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 teacher head, 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

Citations1
Published2008
Admission routes2
Has abstractyes

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