Meandering streamflows across landscapes and scales: a review and discussion
Bibliographic record
Abstract
The study of meandering patterns created by geophysical flows is important for a number of fundamental and applied research topics, including stream and wetland restoration, land management, infrastructure design, oil exploration and production, carbon sequestration, flood-hazard mitigation and planetary palaeoenvironmental reconstructions. This volume, Meandering Streamflows: Patterns and Processes across Landscapes and Scales , contains 13 papers that present field, laboratory and numerical investigations of meandering channels found in distinct environmental and geological contexts and focus on how the interactions of different autogenic and allogenic processes, both in the horizontal and the vertical dimension, affect meander kinematics and the resulting morphology, sedimentology and stratigraphic architecture. In this introductory chapter, we offer an overview of the evolution of scientific research on meandering streams over time, aiming to review and discuss meandering patterns in both fluvial and non-fluvial settings. Additionally, we present a new compilation of data on meander morphological features, drawn from both existing literature and novel sources, encompassing over 8000 meander bends discovered across a diverse array of environments.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".