MétaCan
Menu
Back to cohort
Record W4280505490 · doi:10.1126/sciadv.abj3220

First source-to-sink monitoring shows dense head controls sediment flux and runout in turbidity currents

2022· article· en· W4280505490 on OpenAlexaff
Ed Pope, Matthieu Cartigny, Michael Clare, Peter J. Talling, Gwyn Lintern, Age Vellinga, Sophie Hage, Sanem Açıkalın, Lewis Bailey, Natasha Chapplow, Ye Chen, Joris T. Eggenhuisen, Alison Hendry, Catharina Heerema, Maarten Heijnen, Stephen M. Hubbard, James E. Hunt, Claire McGhee, Daniel R. Parsons, Stephen M. Simmons, Cooper Stacey, Daniela Vendettuoli

Bibliographic record

VenueScience Advances · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsUniversity of VictoriaUniversity of CalgaryGeological Survey of Canada
FundersDurham UniversityNatural Environment Research CouncilSight Research UKLeverhulme Trust
KeywordsTurbidity currentSink (geography)SedimentTurbidityGeologySediment transportTurbulenceTurbiditeGeomorphologyGrain sizeHydrology (agriculture)MechanicsGeotechnical engineeringOceanographySedimentary depositional environmentPhysics

Abstract

fetched live from OpenAlex

Until recently, despite being one of the most important sediment transport phenomena on Earth, few direct measurements of turbidity currents existed. Consequently, their structure and evolution were poorly understood, particularly whether they are dense or dilute. Here, we analyze the largest number of turbidity currents monitored to date from source to sink. We show sediment transport and internal flow characteristic evolution as they runout. Observed frontal regions (heads) are fast (>1.5 m/s), thin (<10 m), dense (depth averaged concentrations up to 38% vol ), strongly stratified, and dominated by grain-to-grain interactions, or slower (<1 m/s), dilute (<0.01% vol ), and well mixed with turbulence supporting sediment. Between these end-members, a transitional flow head exists. Flow bodies are typically thick, slow, dilute, and well mixed. Flows with dense heads stretch and bulk up with dense heads transporting up to 1000 times more sediment than the dilute body. Dense heads can therefore control turbidity current sediment transport and runout into the deep sea.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.777

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.023
GPT teacher head0.269
Teacher spread0.246 · 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 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

Citations54
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueScience AdvancesSame topicGeological formations and processesFrench-language works237,207