Quantification of the relation between surface morphodynamics and subsurface sedimentological product in sandy braided rivers
Bibliographic record
Abstract
Abstract This study uses digital elevation models and ground‐penetrating radar to quantify the relation between the surface morphodynamics and subsurface sedimentology in the sandy braided South Saskatchewan River, Canada. A unique aspect of the methodology is that both digital elevation model and ground‐penetrating radar data were collected from the same locations in 2004, 2005, 2006 and 2007, thus enabling the surface morphodynamics to be tied explicitly to the associated evolving depositional product. The occurrence of a large flood in 2005 also allowed the influence of discharge to be assessed with respect to the process–product relationship. The data demonstrate that the morphology of the study reach evolved even during modest discharges, but more extensive erosion was caused by the large flood. In addition, the study reach was dominated by compound bars before the flood, but switched to being dominated by unit bars during and after the flood. The extent to which the subsurface deposits (the ‘product’) were modified by the surface morphodynamics (the ‘process’) was quantified using the changes in radar‐facies recorded in sequential ground‐penetrating radar surveys. These surveys reveal that during the large flood there was an increase in the proportion of facies associated with bar margin accretion and larger dunes. In subsequent years, these facies became truncated and replaced with facies associated with smaller dune sets. This analysis shows that unit bars generally become truncated more laterally than vertically and, thus, they lose the high‐angle bar margin deposits and smaller scale bar‐top deposits. In general, the only fragments that remain of the unit bars are dune sets, thus making identification of the original unit barform problematic. This novel data set has implications for what may ultimately become preserved in the rock record.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".