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Record W3006214421 · doi:10.1130/g46909.1

Sediment dynamics across gravel-sand transitions: Implications for river stability and floodplain recycling

2020· article· en· W3006214421 on OpenAlexaff
Elizabeth Dingle, Hugh D. Sinclair, Jeremy G. Venditti, Mikaël Attal, Tim Kinnaird, Maggie Creed, Laura Quick, Jeffrey A. Nittrouer, Dilip Gautam

Bibliographic record

VenueGeology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsSimon Fraser University
FundersNatural Environment Research CouncilSight Research UK
KeywordsBed loadSedimentGeologyFloodplainBedformSuspended loadGrain sizeChannel (broadcasting)Hydrology (agriculture)SedimentationSediment transportErosionFlux (metallurgy)AggradationGeomorphologyFluvialGeotechnical engineeringEcology

Abstract

fetched live from OpenAlex

Abstract The gravel-sand transition (GST) is commonly observed along rivers. It is characterized by an abrupt reduction in median grain size, from gravel- to sand-size sediment, and by a shift in sand transport mode from wash load–dominated to suspended bed material load. We documented changes in channel stability, suspended sediment concentration, flux, and grain size across the GST of the Karnali River, Nepal. Upstream of the GST, gravel-bed channels are stable over hundred- to thousand-year time scales. Downstream, floodplain sediment is reworked by lateral bank erosion, particularly during monsoon discharges. Suspended sediment concentration, grain size, and flux reveal counterintuitive increases downstream of the GST. The results demonstrate a dramatic change in channel dynamics across the GST, from relatively fixed, steep gravel-bed rivers with infrequent avulsion to lower-gradient, relatively mobile sand-bed channels. The increase in sediment concentration and near-bed suspended grain size may be caused by enhanced channel mobility, which facilitates exchange between bed and bank material. These results bring new constraints on channel stability at mountain fronts and indicate that temporally and spatially limited sediment flux measurements downstream of GSTs are more indicative of flow stage and floodplain recycling than of continental-scale sediment flux and denudation rate estimates.

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)0.000
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 score0.066
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.021
GPT teacher head0.257
Teacher spread0.237 · 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

Citations42
Published2020
Admission routes1
Has abstractyes

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