Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Vehicular ad hoc networks (VANETs) are essential components of the intelligent transport systems. They are attracting an increasing amount of interest in research and industrial sectors. Vehicular nodes are capable of transporting, sensing, processing information, and wireless communication, which makes them more vulnerable to worm infections than conventional hosts. This survey provides an overview on worm spreading over VANETs. We first briefly introduce the computer worms. Then the V2X communication and applications are discussed from malware and worms propagation perspective to show the indispensability of studying the characteristics of worm propagating on VANETs. The recent literature on worm spreading and containment on VANETs are categorized based on their research methods. The improvements and limitations of the existing studies are discussed. Next, the main factors influencing worm spreading in vehicular networks are discussed followed by a summary of countermeasure strategies designed to deal with these worms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it