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Record W2002013882 · doi:10.1002/esp.2033

A two‐dimensional morphodynamic model of gravel‐bed river with floodplain vegetation

2010· article· en· W2002013882 on OpenAlexaff
S. Samuel Li, Robert G. Millar

Bibliographic record

VenueEarth Surface Processes and Landforms · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of British ColumbiaConcordia University
Fundersnot available
KeywordsFloodplainMeander (mathematics)Point barGeologyRiparian zoneBank erosionVegetation (pathology)Bed loadChannel (broadcasting)Hydrology (agriculture)FluvialInstabilityBankDeposition (geology)GeomorphologyErosionShear stressSediment transportGeotechnical engineeringGeometrySedimentMechanicsGeographyEcology

Abstract

fetched live from OpenAlex

Abstract Artificially straight river channels tend to be unstable, and ultimately develop into river meanders through bank erosion and point‐bar deposition. In this paper account is taken of the effects of riparian and floodplain vegetation on bank strength, floodplain flow resistance, shear stress partitioning, and bedload transport. This is incorporated into an existing 2D hydrodynamic‐morphological model. By applying the new model to an initially straight and single‐threaded channel, the way that its planform and cross‐sectional geometry evolve for different hydraulic and floodplain vegetation conditions is demonstrated. The results show the formation and upstream migration of gravel bars, confluence scouring and the development of meandering and braiding channel patterns. In cases where the channel becomes unstable, the instability grows out of bar formation. The resulting braiding patterns are similar to analytical results. The formation of a transition configuration requires a strong influence from vegetation. Copyright © 2010 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 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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.005
GPT teacher head0.193
Teacher spread0.188 · 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

Citations42
Published2010
Admission routes1
Has abstractyes

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