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Record W4390603235 · doi:10.1029/2023jc020175

Interactions Between Internal Solitary Waves and Sea Ice

2024· article· en· W4390603235 on OpenAlexaff
Sam Hartharn-Evans, Magda Carr, Marek Stastna

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Waterloo
FundersNatural Environment Research Council
KeywordsFloat (project management)MechanicsWavelengthGeologyInternal waveRelative velocityBoundary layerFlow velocityFlow (mathematics)VortexPhysicsGeophysicsMeteorologyOpticsClassical mechanics

Abstract

fetched live from OpenAlex

Abstract Internal Solitary Waves (ISWs) that form on internal density interfaces in the ocean are responsible for the horizontal transport and vertical mixing of heat, nutrients, and other water properties. The waves also induce fluid motion that can induce stresses and motion on floating structures, such as sea ice. This study investigates ISW‐sea ice interactions. Using laboratory experiments, ISWs generated via the lock gate technique are observed interacting with weighted floats of varying sizes. The motion of these floats can be modeled effectively, simply as the average velocity of the fluid under the float, and it is found that when floats are small relative to the wavelength, they behave in the same manner as a fluid particle, but as floats become bigger relative to the wavelength, the maximum velocity decreases, and interaction time increases. This phenomenon is explained simply by the wave‐induced flow as opposed to energy transfer arguments. By using this model with a large sample of theoretical waves, the float motion is parameterized based on the float length and wave parameters. Whilst small floats do not disrupt the flow patterns, the wave‐induced flow under larger floats forms a pair of counter‐rotating vortices at each end of the float. The formation and evolution of these flow features arise as a result of boundary layer separation with the horizontal wave‐induced flow relative to the float velocity. This reveals complex dynamics due to the non‐stationary behavior of both the float and flow.

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 score0.001
Threshold uncertainty score0.002

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 science0.0000.000
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 head0.037
GPT teacher head0.336
Teacher spread0.298 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

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