Physics-based modeling of skier mobility and avalanche rescue in mountainous terrain
Bibliographic record
Abstract
Mobility models play an important role in the evaluation of wireless ad hoc networks. However, most existing mobility models are limited to 1D or 2D user movement. In this paper, we propose a novel 2.5D mobility model suitable for modeling the movement of backcountry skiers in mountainous terrains. These skiers carry wireless devices for communication in the event of emergencies, such as an avalanche, and thus form a dynamic mobile wireless ad hoc network. Our model represents groups of skiers, with each group having an invisible leader who determines the general direction of movement. We calculate the acceleration, velocity, and position of the group leader based on properties of the terrain, gravitational force, and a randomized sine function. To simulate the coordinated mobility of group members, we use a flocking model, which applies cohesion, separation, and alignment forces to influence group members to follow their leader, while avoiding collisions with each other. To demonstrate the applicability of our model, we use simulation to evaluate the skier rescue probability in the event of an avalanche.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".