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Record W4389037191 · doi:10.1029/2023jf007117

Experiments on Gravel‐Sand Transitions: Behavior of the Grain Size Gap Material

2023· article· en· W4389037191 on OpenAlexafffund
Elizabeth Dingle, Jeremy G. Venditti

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGrain sizeSedimentGeologyDeposition (geology)Particle sizeParticle-size distributionMineralogyGeomorphology

Abstract

fetched live from OpenAlex

Abstract River bed sediments often lack fine gravel between 1 and 5 mm, a phenomenon referred to as the “grain size gap.” The gap corresponds to the rapid reduction in grain size associated with the gravel‐sand transition (GST), where median bed material grain size reduces from ∼10 mm gravel to ∼1 mm sand. Fine gravel grain sizes are often present in hillslope sediment, so it is not clear why they are absent on riverbed surfaces. We present a phenomenological laboratory experiment examining changes in sediment dynamics across a GST to examine the behavior of grain size gap material when included in the bed and feed grain size distributions. Our observations indicate that where sand falls out of washload, forming persistent surficial deposits at the GST, grain size gap material experiences enhanced mobility. This is due to hydraulic smoothing by sand that occurs because of a geometric effect, where medium sand bridges interstitial pockets in fine gravel bed surfaces. Our experiments show that gap gravel flux is enhanced by sand deposition, making gravel beds mobile at the threshold of motion. We are unable to maintain an immobile grain size gap gravel bed when sand is fed which explains why gravel beds composed of 1–5 mm particles are so rare on Earth. We hypothesize that in natural systems, grain size gap particles are either buried in the diffuse extension of GSTs or transported into coastal and marine environments where they are more commonly observed.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score0.999

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.053
GPT teacher head0.342
Teacher spread0.289 · 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.

Study designBench or experimental
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

Citations9
Published2023
Admission routes2
Has abstractyes

Explore more

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