Morpho‐sedimentary characteristics of proximal gravel braided river deposits in a Froude‐scaled physical model
Bibliographic record
Abstract
Abstract A Froude‐scaled physical model of a proximal gravel‐bed braided river was used to connect the river morphological characteristics, and sedimentary processes and forms, to deposit geometry. High resolution continuous three‐dimensional topographic data were acquired from sequential photogrammetric digital elevation models paired with grain‐size surface maps derived from image analysis of textural properties of the surface. From these data, the full three‐dimensional development of the braided river deposit and grain‐size sorting patterns was compiled over an experimental time period of 41 h during which the model river reworked a large portion of the braided channel. The minimum surface of the deposit is developed progressively over time by erosion, migration and avulsion of channels, and by local scour at channel confluences. The maximum surface of the deposit is formed by amalgamation of braid bar surfaces and has less overall relief than the minimum surface. Confluence scour constitutes about 5% of the area of the minimum surface. Migration of individual confluences is limited to distances of the order of the width and length of the confluence, so that confluences do not form laterally extensive deposits and basal surfaces. Maximum and minimum surfaces have very similar grain‐size distributions, and there is no extensive basal coarse layer. Deposit maximum thickness is strongly associated with large channel confluences which occur as deeper areas along the main channel belt and make up a large proportion of the thickest portions of the deposit.
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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 | 0.000 | 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".