A Visibility-Driven Approach for Zone Management in Simulations
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
Massively multi-user simulations aim to support a large number of users while keeping the communication among the parties synchronous and highly interactive. In this paper, we present a collaborative virtual architecture that supports a large number of users by dividing the virtual environment into multiple adjacent hexagonal regions in order to manage the interest of the entities. A master node, called a hybrid node, constructs a Peer-to-Peer (P2P) overlay network to connect and manage nodes that lie in its region. Messaging is done at the application layer rather than the network layer, and a node-joining algorithm is proposed to reflect the underlying network physical topology onto the data distribution pathways among the end hosts to enhance the system performance. In addition, the introduction of a buffer zone between adjacent zones reduces the number of connections and disconnections that occur when a node frequently moves at the boundary of the two zones and provides more resilience to the system. We also attempt to shift the messaging among parties in one region from a zone-based method to a visibility-driven method to refine their interest by enabling message filtering. The effectiveness of this collaboration architecture is tested through a prototype implementation and a high level application.
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 | 0.000 | 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 | 0.000 | 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 it