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Sediment Resuspension and Transport by Internal Solitary Waves

2018· article· en· W2886767111 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Fluid Mechanics · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsUniversity of WaterlooQueen's University
Fundersnot available
KeywordsTurbulenceInternal waveGeologySediment transportSedimentReynolds stressBoundary layerOceanographyScale (ratio)Environmental scienceGeophysicsMeteorologyMechanicsGeomorphologyPhysics

Abstract

fetched live from OpenAlex

Large-amplitude internal waves induce currents and turbulence in the bottom boundary layer (BBL) and are thus a key driver of sediment movement on the continental margins. Observations of internal wave–induced sediment resuspension and transport cover significant portions of the world's oceans. Research on BBL instabilities, induced by internal waves, has identified several mechanisms by which the BBL is energized and sediment may be resuspended. Due to the complexity of the induced currents, process-oriented research using theory, direct numerical simulations, and laboratory experiments has played a vital role. However, experiments and simulations have inherent limitations as analogs for oceanic conditions due to disparities in Reynolds number and grid resolution, respectively. Parameterizations are needed for modeling resuspension from observed data and in larger-scale models, with the efficacy of parameterizations based on the quadratic stress largely determining the accuracy of present field-scale efforts.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.826
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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)0.0020.000

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 head0.237
Teacher spread0.227 · 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