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Record W209733812

The fluid dynamics of low-angle river dunes: results from integrated field monitoring, laboratory experimentation and numerical modelling.

2004· other· en· W209733812 on OpenAlexaffabout
Jim Best, Ray Kostaschuk, R. J. Hardy

Bibliographic record

VenueDurham Research Online (Durham University) · 2004
Typeother
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBedformFlow (mathematics)GeologyGeomorphologyComputer simulationUpstream (networking)Flow conditionsSedimentMechanicsSediment transportGeotechnical engineeringPhysicsEngineeringTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Abstract Combined physical and numerical modelling of flow over low-angle river dunes, whose morphology isbased on dunes monitored in the Fraser River, Canada, shows that the flow field is dominated by flowacceleration over the stoss side, flow expansion in the leeside and the absence of a region of permanentflow separation. Both physical and numerical models show the absence of permanent flow separation butsuggest that intermittent flow separation may characterise flow in the leeside. The numerical model isused to investigative the role of upstream inherited flow structure on eddy shedding from the leeside andsuggests that the instantaneous nature of flow, and thus sediment suspension, is dictated by the turbulentflow field in the leeside that is inherently linked to the flow fields of upstream dunes. Turbulencemodulation of flow by the upstream flow field may thus be important for interpreting the flow fields overindividual dunes, highlighting the possible significance of bedform superimposition in bedform dynamics.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

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 communication0.0010.000
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 head0.020
GPT teacher head0.273
Teacher spread0.253 · 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 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

Citations2
Published2004
Admission routes2
Has abstractyes

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