Bibliographic record
Abstract
Among the most visually striking river restoration projects are those that involve the creation of a new channel, often in a new alignment and generally with a form and dimensions that are different from those of the preproject channel. These channel reconstruction projects often have the objective of creating a stable, single-thread, meandering channel, even on rivers that were not historically meandering, on rivers whose sediment load and flow regime would not be consistent with such stable channels, or on already sinuous channels whose bends are not symmetrical. Such meandering channels are often specified by the Rosgen classification system, a popular restoration design approach. Although most projects of this type have not been subject to objective evaluation, completed postproject appraisals show that many of these projects failed within months or years of construction. Despite its, at best, mixed results, this classification and form-based approach continues to be popular because it is easy to apply, because it is accessible to those without formal training in fluvial geomorphology, and probably because it satisfies a deep-seated, although unrecognized, cultural preference for single-thread meandering channels. This preference is consistent with 18th-century English landscape theories, which held the serpentine form to be ideal and led to widespread construction of meandering channels on the country estates of the era. The preference for stability in restored channels seems to be widely accepted by practitioners and funders despite the fact that it is antithetical to research showing that dynamically migrating channels have the greatest ecological richness.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".