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Record W2130447309 · doi:10.1145/985040.985059

Visual specification of behaviours in VRML worlds

2004· article· en· W2130447309 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicComputer Graphics and Visualization Techniques
Canadian institutionsDalhousie University
Fundersnot available
KeywordsVRMLScripting languageComputer scienceJavaScriptXMLThe InternetClass (philosophy)Plug-inWorld Wide WebComputer graphics (images)Human–computer interactionProgramming languageArtificial intelligence

Abstract

fetched live from OpenAlex

The Virtual Reality Modeling Language (VRML) is a textual language used to define objects in 3D worlds, and their behaviours. It is used extensively for providing 3D views and simulations on the internet, through the use of VRML plug-ins. As with languages like HTML or XML, VRML is expressed textually. Although there are a variety of tools allowing for the graphical, interactive definition of 3D objects which can then be exported as VRML text files, definitions of behaviours must be specified textually, generally through short programs written in a scripting language such as JavaScript, connected to the 3D objects using declarations in the VRML file.We are investigating the use of visual programming techniques in an attempt to make it possible for a broader class of users to be able to make use of behaviours in VRML. In this paper we describe our work on showing visual connections between objects, the scripts which control their behaviours, and the objects which control these scripts.

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 score0.845
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.311
Teacher spread0.290 · 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