Bed load transport in managed steep‐gradient headwater streams of southeastern Alaska
Bibliographic record
Abstract
Bed load transport was investigated in four headwater streams in southeastern Alaska subjected to different management and disturbance regimes. Bed load yield was positively correlated to peak discharge during the fall 1999 monitoring period. Fine bed load materials (1–11 mm) that were supplied from hillslope sources were equally mobilized during most storm events. Medium‐sized bed materials (11–200 m) were only partially mobilized even during large storms, whereas large particles (>200 mm) were immobile and often formed interlocking channel structures. The transport distances of medium‐size materials depended on amount of channel obstructions (e.g., woody debris) and sediment supply conditions; both of these factors were influenced by the occurrence of mass movement, timber harvesting, and the related recovery processes. The highest total bed load yield was observed in a channel affected by a debris flow in 1993. Total sediment yields are similar among channels with old‐growth, clear cut (logged 4 years before monitoring), and young alder (affected by landslides and debris flows in 1961) riparian stands. By comparing the old‐growth and young alder channels, it appears that bed load yield recovers from debris flow disturbances in about 40 years; however, recovery of channel conditions (e.g., reach types and woody debris) may take much longer. Effects of timber harvesting on bed load transport are controlled by sediment linkages between hillslopes and channels related to the occurrence of mass movement.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".