Mechanics of viscous wedges: Modeling by analytical and numerical approaches
Bibliographic record
Abstract
Although complex rheological models have been used to study the evolution of orogenic wedges, many features of simple models remain to be fully explained. Here, we analyze the plane strain evolution of model orogenic wedges under simple boundary and rheological conditions. The uniform linear viscosity wedge is driven by motion of a basal boundary at a constant velocity. Three main analysis techniques are used: analytical (algebraic analysis of scales involved), semianalytical (thin sheet approximation), and a complete numerical approach. Application of this variety of approaches provides a better understanding of the underlying physics and outlines the advantages and disadvantages of the different techniques. The evolution of wedges can be divided into three phases. Initially, wedge growth is mainly vertical and symmetrical and depends little on the viscosity. The second phase exhibits almost self‐similar growth with the appearance of surface extension, within an otherwise compressional system, and development of asymmetry. The last phase involves widening of wedge and further development of asymmetry and surface extension, the average slope of wedge decreases during this phase. The Ramberg number, the ratio of characteristic gravitational to shear stress, defines the duration of each phase. Several parameters introduced here (mean surface slope, asymmetry of the wedge, surface extension, and near‐surface strain history) allow observations from natural wedges to be linked to the bulk viscosity of the model wedges. Analysis shows that the thin sheet approximation does not correctly describe the initial stages of wedge evolution.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".