Hydraulic conditions in experimental rill confluences and scour in erodible soils
Bibliographic record
Abstract
Few studies have examined processes active within rill networks or the effect of confluence geometry on rill sediment flux, and it is not clear if observations from river confluences also apply at rill scale. Laboratory experiments were carried out in artificial rectangular rill channels with fixed and erodible beds to identify the effects of confluence geometry on hydraulic conditions and scour patterns. Symmetrical and asymmetrical confluences with angles from 19° to 90° were used. Hydraulic changes in the confluence zone in fixed bed experiments included decreased flow velocity, increased shear velocity, transition from supercritical to subcritical, and from transitional to turbulent flow. Bed scour in the confluence zone resulted, generally increasing with confluence angle, but a more important influence was junction symmetry or asymmetry. Symmetrical confluences produced a symmetrical scour pattern mirroring the original channels, but in asymmetrical confluences scour was more complex, evolving to a symmetrical pattern with confluence angles higher than the original system. Results are consistent with channel evolution to an optimally branched system controlled by minimum power criteria, but validation requires testing with more precise velocity measurement.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".