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Record W2790860932 · doi:10.1002/esp.4362

Changes in the saltation flux following a step‐change in macro‐roughness

2018· article· en· W2790860932 on OpenAlexaff
John A. Gillies, Vicken Etyemezian, George Nikolich, W. G. Nickling, Jasper F. Kok

Bibliographic record

VenueEarth Surface Processes and Landforms · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSurface finishMass fluxMechanicsSurface roughnessParticle sizeMaterials scienceGeometryGeologySoil scienceComposite materialPhysicsMathematics

Abstract

fetched live from OpenAlex

Abstract The effect of a step change in macro‐roughness on the saltation process under sediment supply limited conditions was examined in the atmospheric boundary layer. For an array of roughness elements of roughness density λ = 0.045 ( λ = total element frontal area/total surface area of the array) the horizontal saltation flux was reduced by 90% (±7%) at a distance of ≈150 roughness element heights into the array. This matches the value predicted using an empirical design model and provides confidence that it can be effectively used to engineer roughness arrays to meet sand flux reduction targets. Measurements of the saltation flux characteristics in the vertical dimension, including: saltation layer decay (e‐folding) height and particle size, revealed that with increasing distance into the array, the rate of mass flux change with increasing height decreased notably, and (geometric) mean particle diameter decreased. The distribution of the saltation mass flux in the vertical remains exponential in form with increasing distance into the roughness array, and the e‐folding height increases as well as increasing at a greater rate as particle diameter diminishes. The increase in e‐folding height suggests the height of saltating particles is increasing along with their mean speed. This apparent increase in mean speed is likely due to the preferential removal, or sequestration, of the slower moving particles across the size spectrum, as they travel through the roughness array. Copyright © 2018 John Wiley & Sons, Ltd.

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 score0.172
Threshold uncertainty score0.840

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 studies0.0000.000
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 head0.017
GPT teacher head0.245
Teacher spread0.228 · 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

Citations14
Published2018
Admission routes1
Has abstractyes

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