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Record W4387087213 · doi:10.1130/g51385.1

Controls on upstream-migrating bed forms in sandy submarine channels

2023· article· en· W4387087213 on OpenAlexafffund
Rebecca G. Englert, Age Vellinga, Matthieu Cartigny, Michael Clare, Joris T. Eggenhuisen, Stephen M. Hubbard

Bibliographic record

VenueGeology · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaNatural Environment Research CouncilSight Research UKRoyal Society
KeywordsGeologyTurbidity currentFroude numberSediment transportSubmarineSedimentTurbiditeFlow (mathematics)GeomorphologyBed loadUpstream (networking)Hydrology (agriculture)Geotechnical engineeringOceanographySedimentary depositional environmentMechanics

Abstract

fetched live from OpenAlex

Abstract Submarine channels parallel river channels in their ability to transport sediment. However, in contrast to rivers, sediment transport and bed-form development in submarine channels are less well understood. Many steep (>1°), sandy submarine channels are dominated by upstream-migrating bed forms. The flow conditions required to form these upstream-migrating bed forms remain debated because the interactions between turbidity currents and active bed forms are difficult to measure directly. Consequently, we used a depth-resolved numerical model to test the role of flow parameters that are hypothesized to control the formation of upstream-migrating bed forms in submarine channels. While our modeling results confirmed the importance of previously identified flow parameters (e.g., densiometric Froude number), we found that basal sediment concentration in turbidity currents is the strongest predictor of upstream-migrating bed-form formation. Our model shows how locally steep gradients enable high sediment concentrations (average >5 vol%) in the basal parts of flows, which allow the development of cyclic step instabilities and their associated bed forms. This new insight explains the previously puzzling observation that upstream-migrating bed forms are abundant in proximal, steep, sandy reaches of submarine channels, while their occurrence becomes more intermittent downslope.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
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)0.0030.001

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 head0.019
GPT teacher head0.229
Teacher spread0.211 · 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; both teacher heads agree on what is shown here.

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

Citations12
Published2023
Admission routes2
Has abstractyes

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