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Record W2153358429 · doi:10.1109/mcg.2005.42

Jabiru: Harnessing Java 3D Behaviors for Device and Display Portability

2005· article· en· W2153358429 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

VenueIEEE Computer Graphics and Applications · 2005
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsUniversity of Calgary
FundersNational Science Council
KeywordsComputer scienceJavaSoftware portabilityHuman–computer interactionReal time JavaJava annotationJava appletVirtual realitystrictfpComputer graphicsSet (abstract data type)Java concurrencyComputer graphics (images)Operating systemProgramming language

Abstract

fetched live from OpenAlex

The aim of this paper is to use the Java 3D ConfiguredUniverse utilities to create a set of behaviors that we can integrate into existing Java 3D programs, as long as these programs use the ConfiguredUniverse. We call this behavior package Jabiru (Java 3D Application Behavior Immersive Virtual Reality Utilities). The Jabiru set of behaviors, accessible from a master menu, facilitates moving Java 3D applications originally created for desktop environments to immersive VR environments and vice versa. Jabiru also provides a six-degrees-of-freedom (6DOF) device emulator for a conventional mouse, meant to facilitate offsite testing of immersive VR behaviors on a desktop. The main focus of our work with a CAVE is in relation to bioinformatics, which has embraced Java and Java 3D as one of the choice programming environments. By creating this package, we help bring 3D graphics to both the bioinformatics community and the casual Java 3D developer or user. We discuss the design and implementation of Jabiru.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.849
Threshold uncertainty score0.571

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 head0.017
GPT teacher head0.288
Teacher spread0.271 · 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