How Is Time Distributed in a River Meander Belt?
Bibliographic record
Abstract
Abstract River meandering controls the age of floodplains through its characteristic paces of growth and eventual cutoff of channel bends, forming oxbows. Hence, floodplain‐age distributions should reflect a river's characteristic size and migration rate. This hypothesis has been previously tested in numerical simulations, yet without systematic comparisons with natural systems. Here we analyze oxbow spacing and timescales of bend evolution and abandonment in natural and numerically simulated meander belts. In both cases, a saturated state is achieved whereby oxbows are spaced ∼1 meander radius apart. At saturation, the distribution of floodplain ages and probability of sediment‐storage time can be constrained from characteristic timescales of bend evolution and abandonment. Owing to the similar relationships between floodplain width and characteristic timescales in natural and simulated rivers, we postulate that this approach should apply to unconfined meandering rivers elsewhere—a hypothesis to be tested with independent geo‐ or dendrochronological data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.007 |
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; both teacher heads agree on what is shown here.
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".