Interaction between opposite river bank dynamics
Bibliographic record
Abstract
Although many studies regarding bank erosion and accretion can be found in the literature, it is not common to find works studying the interaction between opposite banks. Some existing morphodynamic models describe bank erosion as an event that depends on near-bank flow and bed topography, as well as on eroding bank properties. Most developed models do not include opposite bank accretion, with the exception of, e.g. Asahi et al. (2013) and Eke et al. (2014). . These models can represent opposite bank dynamics. Analyses of bank-to-bank interactions, showing for instance where the effects of depositing bank push are felt (where exactly opposite bank erosion occurs), are lacking. Observations by Nanson and Hickin (1983) on the Beatton River, in Canada, suggest that bank accretion is important for opposite bank erosion to occur, in addition to the magnitude and duration of hydrological events. The present study focuses on the interaction between opposite river banks. The aim is to describe how bank accretion influences opposite bank erosion and whether there is a spatial lag in this interaction. This paper presents only some preliminary results.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".