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Record W2296393131 · doi:10.1145/1772690.1772933

Enabling WebGL

2010· article· en· W2296393131 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
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsSeneca Polytechnic
Fundersnot available
KeywordsJavaScriptComputer scienceWorld Wide WebHTML5Client-side scriptingWeb pageOpenGLWeb browserWeb contentMultimediaWeb applicationGraphicsWeb APIWeb developmentComputer graphics (images)VisualizationThe Internet

Abstract

fetched live from OpenAlex

WebGL leverages the power of OpenGL to present accelerated 3D graphics on a webpage. The ability to put hardware- accelerated 3D content in the browser will provide a means for the creation of new web based applications that were previously the exclusive domain of the desktop environment. It will also allow the inclusion of features that standalone 3D applications do not have. While WebGL succeeds in bringing the power and low- level API of OpenGL to the browser, it also expects a lot of web developers, who are used to the DOM and JavaScript libraries like jQuery. This paper will look at how mid level APIs can help web developers create unique 3D content that is more than just duplicates of a standalone desktop application on a web page. We will present one such web application named Motionview, built with C3DL, that provides a new means for artist and motion capture studios to communicate with each other. We will also highlight some upcoming project ideas that make use of 3D browser technology in a way that would not have been possible in a desktop environment.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.999

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)0.0280.002

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 head0.201
Teacher spread0.185 · 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

Quick stats

Citations29
Published2010
Admission routes1
Has abstractyes

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