The Friction Coefficient of a Large Ice Block on a Sand/Gravel Beach
Bibliographic record
Abstract
The amount of ice ride-up on beaches and shorelines is a function of the slope of the beach, the driving force, the size of the ice blocks, and the friction between the ice and the beach. Predicting the amount of ride-up is difficult, primarily because little is known about the friction coefficient of large ice blocks on sand/gravel beaches. To investigate this, a test program was performed to measure the friction of a large block of ice sliding on a sand/gravel beach. Four different friction coefficients were measured, corresponding to the four modes of movement of the block on the beach: static, bulldozing, transition and sliding. The friction coefficient decreased as the movement mode changed from static to sliding. The statistical analysis of the friction coefficient values showed that the mean value generally decreased with an increase in velocity. The static friction values were approximately the same for each test. The results of these tests will be presented in this paper, as well as a discussion of the implications of the results on the ride-up processes of ice on these types of shorelines.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".