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Record W2009237393

A Unified Distributed Simulation System

2012· article· en· W2009237393 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

VenueNCSU Libraries Repository (North Carolina State University Libraries) · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceFlexibility (engineering)Distributed computingProcess (computing)Reflection (computer programming)Object (grammar)Distributed algorithmProgramming languageArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Proposes a method for generalizing existing distributed simulation algorithms such as the time warp and Chandy-Misra algorithms to create a unified distributed simulation (UDS) algorithm. Explicitly defining risk and aggressiveness parameters for each model allows models with different behaviors to be mixed within one simulation. The author illustrates how this results in a more powerful environment for creating complex simulations. Current distributed simulation techniques compared. The author relates computational reflection and speculation to the UDS algorithm and details the concurrent object-oriented programming environment created to support Rival, its implementation. UDS extends the functionality of the current distributed simulation techniques. UDS allows components to describe how and when they are willing to receive and process messages and, as a result, gives the user more power and flexibility. >

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.006
Open science0.0010.001
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 head0.041
GPT teacher head0.272
Teacher spread0.231 · 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