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Record W2337524493 · doi:10.1177/1548512915607659

An architecture to facilitate interoperability of Discrete Event System Specification and Coalition Battle Management Language simulation models

2015· article· en· W2337524493 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Defense Modeling and Simulation Applications Methodology Technology · 2015
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsCAE (Canada)Carleton University
Fundersnot available
KeywordsDEVSInteroperabilityComputer scienceDiscrete event simulationEvent (particle physics)High-level architectureCommand and controlInterface (matter)Modeling and simulationArchitectureDistributed computingSoftware engineeringSimulationWorld Wide WebOperating systemTelecommunications

Abstract

fetched live from OpenAlex

The Joint Command, Control and Communications Information Exchange Data Model, Coalition Battle Management Language and Military Scenario Definition Language define formatted schemas that have been developed for use in military simulations. The Discrete Event System Specification (DEVS) is used to create models whose behavior is defined in response to events in the simulated environment. The RESTful Interoperability Simulation Environment (RISE) provides a web-based interface for executing DEVS models. DEVS models can be used to simulate systems as diverse as natural disasters and traffic patterns. We present an application that uses formatted messaging to interact with a DEVS model running on the RISE server. The purpose of this is to demonstrate that a DEVS model can be executed as part of a larger, web-enabled synthetic environment, such as a military planning exercise.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.474
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.113
GPT teacher head0.349
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it