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Record W1969596099 · doi:10.1098/rsta.2012.0366

The possible role of Coriolis forces in structuring large-scale sinuous patterns of submarine channel–levee systems

2013· article· en· W1969596099 on OpenAlexaff
Mathew G. Wells, Remo Cossu

Bibliographic record

VenuePhilosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsTurbidity currentGeologySinuosityEquatorEddyChannel (broadcasting)PhysicsGeometryLatitudeGeomorphologyMechanicsSedimentary depositional environmentGeodesyTurbulence

Abstract

fetched live from OpenAlex

Submarine channel-levee systems are among the largest sedimentary structures on the ocean floor. These channels have a sinuous pattern and are the main conduits for turbidity currents to transport sediment to the deep ocean. Recent observations have shown that their sinuosity decreases strongly with latitude, with high-latitude channels being much straighter than similar channels near the Equator. One possible explanation is that Coriolis forces laterally deflect turbidity currents so that at high Northern latitudes both the density interface and the downstream velocity maximum are deflected to the right-hand side of the channel (looking downstream). The shift in the velocity field can change the locations of erosion and deposition and introduce an asymmetry between left- and right-turning bends. The importance of Coriolis forces is defined by two Rossby numbers, RoW=U/Wf and RoR=U/Rf, where U is the mean downstream velocity, W is the width of the channel, R is the radius of curvature and f is the Coriolis parameter. In a bending channel, the density interface is flat when RoR∼-1, and Coriolis forces start to shift the velocity maximum when |RoW|<5. We review recent experimental and field observations and describe how Coriolis forces could lead to straighter channels at high latitudes.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.123
Threshold uncertainty score0.218

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)0.0000.000

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 head0.009
GPT teacher head0.189
Teacher spread0.180 · 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 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

Citations35
Published2013
Admission routes1
Has abstractyes

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Same venuePhilosophical Transactions of the Royal Society A Mathematical Physical and Engineering SciencesSame topicGeological formations and processesFrench-language works237,207