On the relevance of alpha-hulls to the boundary detection problem in sensor networks
Bibliographic record
Abstract
Intuitively, many wireless and sensing applications benefit from knowledge of network boundaries. Many virtual coordinate constructions rely on the furthest set of nodes as beacons. Network edges may also bound routing holes in the network, regions of failure due to environmental effects, or indicate the need for additional deployment. In this paper we explore the potential to solve the edge detection problem using a geometric structure called the alpha-shape (alpha-shape). For a disc of radius 1/alpha, the alpha-shape consists of nodes (and joining edges) that sit on the boundary of the discs that contain no other nodes in the network. In addition to geometry-related fields of study such as graphics and computational geometry, alpha-shapes have been used in the disciplines of molecular biology, particle physics, and others. We explore the relationship between the alpha parameter and radio communication range and show that, by setting the alpha parameter appropriately, it is possible to compute the network alpha-shape locally.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".