MétaCan
Menu
Back to cohort
Record W2987339190 · doi:10.1145/3355047.3359423

Dataflow programming and processing for artists and beyond

2019· article· en· W2987339190 on OpenAlexafffund
Serguei A. Mokhov, Miao Song, Sudhir P. Mudur, Peter Grogono

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHuman Motion and Animation
Canadian institutionsConcordia University
FundersConcordia University of Edmonton
KeywordsComputer scienceShaderDataflowComputer graphics (images)GraphicsOpenGLMultimediaInteractivityEntertainmentHuman–computer interactionOperating systemVisualizationVisual artsArtificial intelligence

Abstract

fetched live from OpenAlex

We complement the last three editions of the course at SIGGRAPH Asia (2015, 2016, 2018) and SIGGRAPH (2017) to make it more of a hands-on nature and include OpenISS. We explore a rapid prototyping of interactive graphical applications for stage and beyond using Jitter/Max and Processing with OpenGL, shaders, and featuring connectivity with various devices. Such rapid prototyping environment is ideal for entertainment computing, as well as for artists and live performances using real-time interactive graphics. We share the expertise we developed in connecting the real-time graphics with on-stage performance with the Illimitable Space System (ISS) v2 and its OpenISS core framework for creative near-realtime broadcasting, and the use of AI and HCI techniques in art.

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.

How this classification was reachedexpand

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.976
Threshold uncertainty score0.125

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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes2
Has abstractyes

Explore more

Same topicHuman Motion and AnimationFrench-language works237,207