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Record W2092006679 · doi:10.1109/mcg.2015.14

Future Directions in Computer Graphics and Visualization: From CG&A's Editorial Board

2015· article· en· W2092006679 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 · 2015
Typearticle
Languageen
FieldComputer Science
TopicComputer Graphics and Visualization Techniques
Canadian institutionsSimon Fraser UniversityUniversity of Victoria
FundersArgonne National LaboratoryBattelleU.S. Department of EnergyPacific Northwest National LaboratoryNational Science Foundation
KeywordsAudience measurementVisionEditorial boardComputer scienceComputer graphicsGraphicsVisualizationDisciplineWorld Wide WebLibrary scienceComputer graphics (images)SociologyPolitical scienceLawArtificial intelligence

Abstract

fetched live from OpenAlex

With many new members joining the CG&A editorial board over the past year, and with a renewed commitment to not only document the state of the art in computer graphics research and applications but to anticipate and where possible foster future areas of scientific discourse and industrial practice, CG&A asked its editorial and advisory council members about where they see their fields of expertise going. The answers compiled here aren't meant to be all encompassing or deterministic when it comes to the opportunities computer graphics and interactive visualization hold for the future. Instead, the goal is to give a more in-depth introduction of members of the editorial board to the CG&A readership and encourage cross-disciplinary discourse toward approaching, complementing, or disputing the visions laid out in this compilation. Here's what the CG&A editorial and advisory council members had to say.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.025
GPT teacher head0.296
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