Grain-Size Controls On the Morphology and Internal Geometry of River-Dominated Deltas
Bibliographic record
Abstract
Abstract: Predictions of a delta's morphology, facies, and stratigraphy are typically derived from its relative wave, tide, and river energies, with sediment type playing a lesser role. Here we test the hypothesis that, all other factors being equal, the topset of a relatively noncohesive, sandy delta will have more active distributaries, a less rugose shoreline morphology, less topographic variation in its topset, and less variability in foreset dip directions than a highly cohesive, muddy delta. As a consequence its stratigraphy will have greater clinoform dip magnitudes and clinoform concavity, a greater percentage of channel facies, and less rugose sand bodies than a highly cohesive, muddy delta. Nine self-formed deltas having different sediment grain sizes and critical shear stresses required for re-entrainment of mud are simulated using Deflt3D, a 2D flow and sediment-transport model. Model results indicate that sand-dominated deltas are more fan-shaped while mud-dominated deltas are more birdsfoot in planform, because the sand-dominated deltas have more active distributaries and a smaller variance of topset elevations, and thereby experience a more equitable distribution of sediment to their perimeters. This results in a larger proportion of channel facies in sand-dominated deltas, and more uniformly distributed clinoform dip directions, steeper dips, and greater clinoform concavity. These conclusions are consistent with data collected from the Goose River Delta, a coarse-grained fan delta prograding into Goose Bay, Labrador, Canada. A reinterpretation of the Kf-1 parasequence set of the Cretaceous Last Chance Delta, a unit of the Ferron Sandstone near Emery, Utah, USA uses Ferron grain-size data, clinoform-dip data, clinoform concavity, and variance of dip directions to hindcast the delta's planform. The Kf-1 Last Chance Delta is predicted to have been more like a fan delta in planform than a birdsfoot delta.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".