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
Abstract The IEEE 1516 Standard ‘High Level Architecture (HLA)’ and its implementation ‘Run‐Time Infra‐structure (RTI)’ defines a general‐purpose network communication mechanism for Distributed Interactive Simulation (DIS). However, it does not address real‐time requirements of DIS. Current operating system technologies can provide real‐time processing through some real‐time operating systems (RTOSs) and the Internet is also moving to an age of Quality of Service (QoS), providing delay and jitter bounded services. With the availability of RTOSs and IP QoS, it is possible for HLA to be extended to take advantage of these technologies in order to construct an architecture for Real‐Time DIS (RT‐DIS). This extension will be a critical aspect of applications in virtual medicine, distributed virtual environments, weapon simulation, aerospace simulation and others. This paper outlines the current real‐time technology with respect to operating systems and at the network infrastructure level. After summarizing the requirements and our experiences with RT‐DIS, we present a proposal for HLA real‐time extension and architecture for real‐time RTI. Similar to the growth of real‐time CORBA (Common Object Request Broker) after the mature based CORBA standard suite, Real‐Time HLA is a natural extension following the standardization of HLA into IEEE 1516 in September 2000. Copyright © 2004 John Wiley & Sons, Ltd.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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