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Record W31957583

SPATIAL AND TEMPORAL VARIABILITY IN INTENSITY OF AEOLIAN TRANSPORT ON A BEACH AND FOREDUNE

2015· article· en· W31957583 on OpenAlexaboutno aff
Robin Davidson‐Arnott, Jeff Ollerhead, Patrick A. Hesp, Ian J. Walker

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsnot available
Fundersnot available
KeywordsForeduneAeolian processesSediment transportGeologyWind speedAnemometerHydrology (agriculture)GeomorphologyAtmospheric sciencesSedimentOceanographyGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

Abstract: This paper presents results from measurements of the intensity of sand transport by wind on the beach and stoss slope of a vegetated foredune over one day, at Greenwich Dunes, Prince Edward Island, Canada. Measurements of wind speed and direction were made with arrays of cup anemometers and 2-D sonic anemometers. Sediment transport intensity was measured at a height of 2-4 cm above the bed using 6 Sabatech omnidirectional saltation probes which count the impact of saltating grains on a piezoelectric crystal. Individual sensors appear to provide a consistent response to fluctuating sand transport. Where there is a considerable supply of dry sand the saltation system responds very rapidly (1-2 seconds) to fluctuations in wind speed- i.e. to wind gusts. Where sand supply from the surface is limited by moisture or by the presence of vegetation, mean transport rates are much lower and this reflects both a reduction in the instantaneous transport rate and in a transport system that becomes increasingly intermittent. While at this stage the saltation probes cannot provide a reliable estimate of the total sediment flux, they do provide a useful insight into the nature of the transport

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.241
Teacher spread0.198 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

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