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Record W1573683211 · doi:10.1109/qomex.2015.7148136

The effect of sound on visual realism perception and task completion time in a cel-shaded serious gaming virtual environment

2015· article· en· W1573683211 on OpenAlexaff
David Rojas, Brent Cowan, Bill Kapralos, Karen Colllins, Adam Dubrowski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsMemorial University of NewfoundlandOntario Tech UniversityUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsPerceptionTask (project management)RealismComputer scienceSound (geography)Human–computer interactionVirtual realityVirtual machineMultimediaComputer visionPsychologyAcousticsEngineering

Abstract

fetched live from OpenAlex

Here we investigate the effect of sound on the perception of visual realism and the time required to complete a simple navigation-based task within a serious gaming (virtual) environment under various sound and visual conditions. Results indicate that the perception of visual realism and task completion time can be affected by sound. Designers and developers of serious games (and virtual environments in general) should be aware of the effects of sound on a user's perception of the visual scene and on task completion time, and they should thus ensure that sound is carefully considered when creating such environments.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.324
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2015
Admission routes1
Has abstractyes

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