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Record W2971473675 · doi:10.1145/3337722.3337740

SuBViS

2019· article· en· W2971473675 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
TopicUsability and User Interface Design
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsComputer scienceScripting languageWorkflowProcess (computing)BlueprintIterative and incremental developmentSoftware engineeringHuman–computer interactionGraphMultimediaProgramming languageDatabaseEngineeringTheoretical computer science

Abstract

fetched live from OpenAlex

Game development is a naturally iterative process where many ideas are tested and prototyped before final decisions are made. Given the increased usage of visual scripting systems in game development recently, it is apparent that these tools must be able to support every aspect of this process. One aspect that is not well captured is the exploration of alternatives. SuBViS was developed as a solution to this problem. It is a visual scripting system for exploring parallel ideas in game development through the use of alternatives at graph and node levels. These two levels of exploring alternatives can be combined or used separately. This paper presents a use case example, which demonstrates how SuBViS can improve workflow and communication between team members. It also discusses a small-scale user study and the results obtained therein. SuBViS was developed on top of Unreal Engine's existing Blueprint Visual Scripting system.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.844
Threshold uncertainty score0.996

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)0.0010.005

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 head0.009
GPT teacher head0.208
Teacher spread0.199 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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