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Record W2134047137 · doi:10.1002/esp.1658

Defining and measuring braiding intensity

2008· article· en· W2134047137 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEarth Surface Processes and Landforms · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaParks Canada
KeywordsSinuosityFlumeChannel (broadcasting)BraidStatisticsHydrographHydrology (agriculture)Scale (ratio)MathematicsSampling (signal processing)Sensitivity (control systems)GeometryGeologyFlow (mathematics)Computer scienceGeotechnical engineeringGeographyCartography

Abstract

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Abstract Geomorphological studies of braided rivers still lack a consistent measurement of the complexity of the braided pattern. Several simple indices have been proposed and two (channel count and total sinuosity) are the most commonly applied. For none of these indices has there been an assessment of the sampling requirements and there has been no systematic study of the equivalence of the indices to each other and their sensitivity to river stage. Resolution of these issues is essential for progress in studies of braided morphology and dynamics at the scale of the channel network. A series of experiments was run using small‐scale physical models of braided rivers in a 3 m ∞ 20 m flume. Sampling criteria for braid indices and their comparability were assessed using constant‐discharge experiments. Sample hydrographs were run to assess the effect of flow variability. Reach lengths of at least 10 times the average wetted width are needed to measure braid indices with precision of the order of 20% of the mean. Inherent variability in channel pattern makes it difficult to achieve greater precision. Channel count indices need a minimum of 10 cross‐sections spaced no further apart than the average wetted width of the river. Several of the braid indices, including total sinuosity, give very similar numerical values but they differ substantially from channel‐count index values. Consequently, functional relationships between channel pattern and, for example, discharge, are sensitive to the choice of braid index. Braid indices are sensitive to river stage and the highest values typically occur below peak flows of a diurnal (melt‐water) hydrograph in pro‐glacial rivers. There is no general relationship with stage that would allow data from rivers at different relative stage to be compared. At present, channel count indices give the best combination of rapid measurement, precision, and range of sources from which measurements can be reliably made. They can also be related directly to bar theory for braided pattern development. Copyright © 2008 John Wiley & Sons, Ltd.

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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 score0.039
Threshold uncertainty score0.377

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 head0.014
GPT teacher head0.193
Teacher spread0.179 · 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