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Record W2909859055 · doi:10.1029/2018jf004835

The Growth of Dunes in Rivers

2019· article· en· W2909859055 on OpenAlexafffund
R. W. Bradley, Jeremy G. Venditti

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFlumeSediment transportGeologyFlow (mathematics)Constant (computer programming)Entrainment (biomusicology)Stage (stratigraphy)SedimentExponential growthSeries (stratigraphy)GeomorphologyMechanicsMathematicsPhysicsPaleontologyComputer scienceMathematical analysis

Abstract

fetched live from OpenAlex

Abstract Dune response to variable flow has been well documented, but there is no universal model to predict dune dimensions as they respond to imposed flows. Here we use a series of flume experiments to explore dune growth in response to constant flow to better understand the form of dune growth curves. Observations of dune growth from a flat sand bed were made at three flow depths, under five different constant transport stages in a laboratory flume. The transport stages ranged from the sediment entrainment threshold to suspension conditions. The bed was flattened before each run and topography was continually mapped, providing observations of dune growth and morphology at each distinct transport stage condition. The results show that dune growth curves exhibited three different behaviors: (1) exponential growth; (2) punctuated growth, when a period of initially linear growth was abruptly interrupted by exponential growth; and (3) instantaneous growth, when bed evolution happened so quickly that we were unable to take measurements of the phenomenon. Growth behavior is dependent on the applied transport stage, and the time for a growing dune field to reach equilibrium decreases nonlinearly with transport stage. Observations of evolving dunes and the time required to achieve an equilibrium bed state are used to propose a series of relations that can predict dune dimensions through time.

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)0.002
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 score0.028
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.017
GPT teacher head0.285
Teacher spread0.268 · 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

Citations35
Published2019
Admission routes2
Has abstractyes

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