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Record W2892393537 · doi:10.1029/2018jf004847

Introducing Finer Grains Into Bedload: The Transition to a New Equilibrium

2018· article· en· W2892393537 on OpenAlexafffund
Ashley Dudill, Hugo Lafaye de Micheaux, Philippe Frey, Michael Church

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of British ColumbiaBC Hydro (Canada)
FundersInstitut national des sciences de l'UniversNatural Sciences and Engineering Research Council of CanadaInstitut National de Recherche en Sciences et Technologies pour l'Environnement et l'AgricultureAgence Nationale de la Recherche
KeywordsAggradationFlumeGrain sizeBed loadSortingSedimentGeologyChannel (broadcasting)Soil scienceFlow (mathematics)MineralogyMechanicsMaterials scienceSediment transportGeomorphologyMathematicsPhysics

Abstract

fetched live from OpenAlex

Abstract Simplified experiments on fine grain inputs to a coarse bed in mobile equilibrium were undertaken in a small, steep, narrow flume using spherical glass particles to study the influence upon the channel response of the size ratio between the bed ( D c ) and the input fines ( D f ). Size ratios ( D c / D f ) between 7.14 and 1.25 were tested, with a constant flow and coarse sediment feed rate and a variety of fine and total feed rates. Transition to a new, two‐size equilibrium occurs through slope adjustment (aggradation/degradation), accompanying a change in sediment mobility created by the addition of the fine material. Previous work has documented superior mobility following a fine grain input; the present experiments identify limits of this behavior related to the fine grain size, the proportion of fines introduced, and the total sediment supply. The mechanistic reasons for these limits are examined with respect to the grain sorting behavior, leading to the development (or not) of a quasi‐static layer of the fine material at the base of the transport layer. Despite the variation in bed slope response depending upon these factors, the slope transitions consistently follow an exponential profile.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.314
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; both teacher heads agree on what is shown here.

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

Citations30
Published2018
Admission routes2
Has abstractyes

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