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Record W2044833864 · doi:10.1504/ijspm.2014.064384

A prototype for project management game development using high level architecture

2014· article· en· W2044833864 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

VenueInternational Journal of Simulation and Process Modelling · 2014
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGame development toolComputer scienceBiddingGame DeveloperGame programmingGame designGame design documentVideo game developmentLift (data mining)ArchitectureLevel designProject managementEngineering managementHuman–computer interactionSoftware engineeringSystems engineeringEngineering

Abstract

fetched live from OpenAlex

Construction games teach students various concepts of managing project risks, making critical resource allocation and utilisation decisions, activity sequencing and other related construction issues. Past game development environments range from programs running monolithically on standalone computers to synthetic environments that support distributed modules (programs) running concurrently on different computers. This paper discusses one such environment, the construction synthetic environment (COSYE) based on high level architecture (HLA), which has potential as a game development environment. Then a framework for developing project management games within COSYE is proposed, based on experiences from previous game developments. Examples of games discussed include the bidding game, a tunnelling game and a crane lift planning game. This framework is meant to simplify game development. The paper highlights specifications for an administrator, a player and a simulator module.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.757
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.095
GPT teacher head0.349
Teacher spread0.255 · 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