Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".