Bibliographic record
Abstract
Basal sliding is one of the most important components in the dynamics of fast–flowing glaciers, but remains poorly understood on a theoretical level. In this paper, the problem of glacier sliding with cavitation over hard beds is addressed in detail. First, a bound on drag generated by the bed is derived for arbitrary bed geometries. This bound shows that the commonly used sliding law, τ b = Cu m b N n , cannot apply to beds with bounded slopes. In order to resolve the issue of a realistic sliding law, we consider the classical Nye–Kamb sliding problem, extended to cover the case of cavitation but neglecting regelation. Based on an analogy with contact problems in elasticity, we develop a method which allows solutions to be constructed for any finite number of cavities per bed period. The method is then used to find sliding laws for irregular hard beds, and to test previously developed theories for calculating the drag generated by beds on which obstacles of many different sizes are present. It is found that the maximum drag attained is controlled by those bed obstacles which have the steepest slopes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".