Morphodynamic styles: a novel index of gravel-bed river behaviour
Bibliographic record
Abstract
The interaction between form and process within a river produces the variety of morphodynamics we observe in channels. This poster presents a method using a simple index of channel behaviour that quantitatively represents the style of deformation a river reach undergoes. We term this index the throughput ratio (ζ), and it is calculated by comparing the volume of morphologic change recorded during an event to the volume of sediment transported during the event. The ratio of these two volumes represents a change in behaviour from exchange-based deformation of the channel (ζ < 1) to a more resilient throughput channel state where material is sourced from upstream, does not interact with the reach in question and is transmitted through (ζ > 1). A pair of experiments that developed different morphodynamics whilst sharing the same initial width, slope, discharge and grain size were used to demonstrate this methodology and interpretation of the results. The difference in morphodynamics between the channels was due to the presence of inerodible banks in one experiment, and a freedom to widen in the other. The inclusion of fixed banks prevented the system from being able to adjust its channel cross-section as freely, and maintained a high but variable sediment throughput over the experiment. In the system with mobile banks, the channel widened and exhibited a greater capacity to store sediment inside and outside of the active channel, causing the sediment transport rate to decline to zero during the experiment. In both, the rate of morphologic change tended to zero despite their marked differences in sediment transport over time. As a result, the throughput ratios depict two contrasting evolutions of channel behaviour. The differences in trajectory are due to the processes available to each system and their feedback with channel form. This approach provides a new method of representing channel character that may act to supplement existing analyses of river behaviour.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| 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".