Bibliographic record
Abstract
In this paper, we introduce novel motion-based routing protocols for opportunistic packet relay in ad-hoc opportunistic networks. Unlike existing ad-hoc routing protocols, which require global knowledge about the mobility patterns of other nodes, thus raising scalability and privacy concerns, our routing protocols store and use only local motion information, such as the current direction of the local node. Such in- formation is easily obtainable by any modern GPS-equipped mobile device. We design and evaluate a series of protocols using different motion information, ranging from simple, easy to capture metrics i.e., speed and direction, to more complex metrics, i.e., the past or expected trajectory of the local node. These metrics allow for increasing degrees of routing accuracy at a correspondingly higher cost in terms of memory and computation. However, all of our routing protocols have constant complexity in the size of the network, and none of them rely on nodes sending or storing information about other for- warding nodes. This makes our schemes ideal for large-scale networks and non-community networks, where membership is very dynamic.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".