MétaCan
Menu
Back to cohort
Record W2003538822 · doi:10.1142/s0218194007003367

PROTECT VIRTUAL PROPERTY IN ONLINE GAMING SYSTEM

2007· article· en· W2003538822 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 Software Engineering and Knowledge Engineering · 2007
Typearticle
Languageen
FieldComputer Science
TopicCryptography and Data Security
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsComputer scienceEntertainmentProperty (philosophy)TRACE (psycholinguistics)MetaverseVirtual worldOrder (exchange)Virtual economyComputer securityVirtual realityMultimediaInternet privacyHuman–computer interactionWorld Wide WebBusiness

Abstract

fetched live from OpenAlex

Massively multiplayer role-playing gaming (MMORPG) has become a very popular entertainment in Asia. Along with the success of the massively multiplayer role-playing gaming industry in Asia, online gaming-related crimes have grown at an amazing rate. Most of the criminal cases are related to virtual properties since markets have developed for the virtual properties giving them real world values. There has been little research and resulting technologies for MMORPG virtual property protection. In order to reduce the crimes and protect online gaming systems, one potential solution is protecting the virtual properties in online gaming systems. In this paper, we propose a virtual property management language to meter the use of virtual property. The language provides a framework for managing the use of virtual properties and recording the history of transactions to trace the life of virtual properties.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.727
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.007
GPT teacher head0.226
Teacher spread0.218 · 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