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Record W2444550892 · doi:10.1002/2016gl069579

Acoustic observations of near‐bed sediment concentration and flux statistics above migrating sand dunes

2016· article· en· W2444550892 on OpenAlexafffund
G. Wilson, Alex E. Hay

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSedimentGeologyMass fluxFlux (metallurgy)Sediment transportAcoustic Doppler current profilerBed loadFlow (mathematics)GeomorphologyMechanicsCurrent (fluid)PhysicsOceanography

Abstract

fetched live from OpenAlex

Abstract A coherent Doppler profiler was used to measure coincident time series of velocity (u,w), sediment mass concentration (c), and sediment grain size (d), above mobile sand dunes in unidirectional flow (∼1 m/s, ∼1 m water depth). The measurements are used to extract statistical distributions of sediment concentration and flux just above the bed. Observed mass fluxes (uc,wc) were well fit by quasi‐exponential distributions, at all positions along the dune profile, similar to previous observations of single‐particle momenta for bed load over flat beds. Observed concentrations of moving particles were well fit by negative‐binomial distributions, also similar to previous observations over flat beds. These probability distributions relate to two recent stochastic theories, previously derived and verified for uniform flow over flat beds. It is hypothesized that these theories may also be used as a local approximation in natural‐scale flows with bed forms.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.029
GPT teacher head0.287
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2016
Admission routes2
Has abstractyes

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