MétaCan
Menu
← Back to cohort
Record W4321500626 · doi:10.5194/egusphere-egu23-1766

Numerical analysis of breather interactions

2023· preprint· en· W4321500626 on OpenAlexaff
Keisuke Nakayama, Kevin G. Lamb

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBreatherNonlinear systemOvertakingCollisionAmplitudePhysicsKorteweg–de Vries equationMathematical analysisSolitonClassical mechanicsMathematicsQuantum mechanicsEngineeringComputer science

Abstract

fetched live from OpenAlex

While the existence of breathers in the ocean is not clearly revealed, Rouvinskaya et al. (2015) suggested the possibility that breathers occurred in the Baltic Sea. In three-layer symmetric stratifications with the same density difference across each interface, the modified KdV equation (the Gardner equation with the quadratic nonlinear coefficient equal to zero) predicts that breathers exist. Therefore, the soliton-like characteristics of fully nonlinear breathers must be better understood. Thus, this study used fully nonlinear numerical simulations to investigate breather interactions by analysing overtaking collisions of two breathers in a three-layer fluid. As a result, an overtaking collision of two breathers is almost elastic when the ratio of the breather amplitude to the upper and lower layer thickness is smaller. Furthermore, the collision is found to remove the mode-2 structure, resulting in a significant role in forming breathers.

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)0.002
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0040.000

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 head0.030
GPT teacher head0.263
Teacher spread0.233 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicOceanographic and Atmospheric Processes→French-language works237,207→