Physiographically controlled allometry of specific sediment yield in the canadian cordillera: a lake sediment‐based approach
Bibliographic record
Abstract
It is generally supposed that specific sediment yield declines as the drainage basin area increases, as part of the mobilized sediment becomes trapped in the downstream cascade of storage zones. In British Columbia, using fluvial suspended sediment load data, Church and Slaymaker (Nature 1989, Vol 337, pp. 452–454) have observed a pattern of increasing specific sediment yield at all spatial scales up to 3×104km2. This trend has been attributed to the dominance of secondary remobilization of Quaternary sediments over primary denudation of the land surface. Using a larger data set of lake sediment‐based estimates of long‐term sediment yield, sub‐regional patterns of specific yield have been investigated for the Canadian Cordillera. Between spatial scales of 0.9 and 190 km2 sediment yield trends are differentiated by physiography, as indicated by the variable allometry observed in the specific sediment yield–drainage basin area relations. Highest sediment yields were observed in the Coast Mountains where specific sediment yields conform to the regional pattern described by Church and Slaymaker. However, in flat‐lying plateau and major valley areas specific sediment yield decreases with increasing drainage area, thus conforming to the conventional model of sediment delivery. In several other sub‐regions of intermediate relief there were no significant relations between specific yield and drainage area. These results suggest that no single model of sediment yield is adequate to describe sediment transfer processes in the Canadian Cordillera at the sub‐regional scale.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".