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Record W4210897654 · doi:10.1002/esp.5335

Covariation in width and depth in bedrock rivers

2022· article· en· W4210897654 on OpenAlexafffund
Morgan Wright, Jeremy G. Venditti, Tingan Li, Max Hurson, Shawn Chartrand, Colin D. Rennie, Michael Church

Bibliographic record

VenueEarth Surface Processes and Landforms · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of British ColumbiaUniversity of OttawaSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBedrockCanyonAlluviumGeologyGeomorphologyChannel (broadcasting)Hydrology (agriculture)Geotechnical engineering

Abstract

fetched live from OpenAlex

Abstract The width and depth of rivers are generally inversely related. For a given discharge, wider rivers tend to be shallower than narrower rivers, which are correspondingly deeper. This is particularly true in bedrock and mixed bedrock–alluvial channels, where deep pools occur downstream of lateral constrictions, downstream of which the channel becomes wider and shallower. However, covariation of width and depth in bedrock and mixed bedrock–alluvial rivers has never been explored due to the lack of field measurements. Here we present a 375 km survey of width and depth measurements in the Fraser Canyon, British Columbia, which alternates irregularly among alluvial (no bedrock exposed on either bank), bedrock‐constrained (bedrock exposed on one bank), and bedrock‐bound (bedrock exposed on both banks) sections. We find that bedrock‐bound reaches have the deepest and narrowest sections, followed by bedrock‐constrained reaches and alluvial reaches, which feature the shallowest and widest sections of channel. There is an inverse relation between width and depth for all the channels, with alluvial channels having the highest correlation between these two variables, and thus the greatest covariance. We further explore the relation between width and depth and the downstream hydraulic geometry of 42 individual bedrock‐bound canyons. There is an inverse relation between canyon width and depth, with substantial variation within individual canyons. The downstream hydraulic geometry for these bedrock‐bound canyons does not follow that typical of alluvial channels; depth is the only variable that adjusts substantially as a response to increasing discharge and upstream basin area.

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 score0.014
Threshold uncertainty score0.688

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)0.0010.000

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 head0.006
GPT teacher head0.197
Teacher spread0.191 · 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

Citations16
Published2022
Admission routes2
Has abstractyes

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