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Record W4229032889 · doi:10.1029/2021jf006456

Experiments on Pool Formation in Bedrock Canyons

2022· article· en· W4229032889 on OpenAlexafffund
Zhihao Cao, Jeremy G. Venditti, Tingan Li

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsSimon Fraser UniversityGolder Associates (Canada)
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsCanyonAlluviumGeologyBedrockErosionSediment transportSedimentHydrology (agriculture)GeomorphologyBed loadChannel (broadcasting)Geotechnical engineering

Abstract

fetched live from OpenAlex

Abstract Rivers cut into rock exhibit a wide range of morphologies that do not occur in alluvial rivers. The reach‐scale morphology of bedrock canyons has not been widely explored. Many rivers bound by rock on both banks exhibit a constriction‐pool‐widening morphology characterized by a lateral channel constriction, a deeply scoured pool that typically forms downstream of the constriction, and a channel widening coincident with the scour pool. Lateral constrictions are thought to cause plunging flows that carve pools which then shallow and widen downstream. A flume experiment was conducted to test this hypothesis. Experiments show that flow deceleration upstream of the constricted canyon promotes alluviation. Flow acceleration through the canyon prevents persistent alluvium from developing before a pool is formed. At the canyon entrance, flow and sediment plunge toward the bed, creating a primary scour pool. The primary scour pool reaches equilibrium morphology for a given constant discharge and sediment supply by cutting a slot, which then gets deep enough to maintain a permanent alluvial cover, protecting the pool from further vertical erosion. Downstream of the primary pool, an alluvial cover intermittently develops that causes flow to plunge, carving secondary pools. Shear stresses are counterintuitively large in alluviated areas and low in places where the bed is clear of sediment. However, near‐bed velocity was strongly correlated with alluviation patterns and erosion rate, suggesting near‐bed velocity may be a more practical way to calculate rock erosion rates in non‐uniform flows.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.041
GPT teacher head0.331
Teacher spread0.290 · 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 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

Citations9
Published2022
Admission routes2
Has abstractyes

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